{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Voxel GC Stats\n",
    "\n",
    "Quantitatively evaluating the memory consumption and accuracy of our reconstructions post voxel decay.\n",
    "\n",
    "Goals:\n",
    " * Show memory usage goes down with the threshold k\n",
    " * Show accuracy is OK, and maybe only goes down a little\n",
    " * Show that completeness only goes down a little with super k-s\n",
    " * It's probably best to have side-by-side plots of DispNet and ELAS\n",
    " \n",
    " \n",
    "Technical:\n",
    " * If you get an error like \"FileNotFoundError: [Errno 2] No such file or directory: 'dvipng'\",\n",
    " running `sudo apt install dvipng` should help.\n",
    " * If you get LaTeX rendering errors from matplotlib, make sure you have an up-to-date LaTeX\n",
    " installation on your system. It is required for the LaTeX plot labels.\n",
    " * Other plotting erros can be solved by ensuring the notebook is Trusted (top-right in Jupyter),\n",
    " since matplotlib needs to access various system utilities to render formats like EPS (IIRC)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import os\n",
    "import sys\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "from matplotlib import rc\n",
    "\n",
    "# Enable full LaTeX support in plot text. Requires a full-fledged LaTeX installation\n",
    "# on your system, accessible via PATH.\n",
    "rc('text', usetex=True)\n",
    "\n",
    "def set_plot_font_size(size):\n",
    "    matplotlib.rcParams.update({'font.size': size})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This root assumes you are running this notebook with the 'notebooks'\n",
    "# folder as the working directory.\n",
    "root = os.path.join('..', 'csv', 'decay-experiments')\n",
    "\n",
    "fig_dir = os.path.join(root, '..', '..', 'fig')\n",
    "if not os.path.isdir(fig_dir):\n",
    "    os.mkdir(fig_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stitch(base_tpl):\n",
    "    \"\"\"Used to stitch together data from multiple CSV dumps.\n",
    "    \n",
    "    Useful if you want X frames but the system crashes from a stupid bug\n",
    "    when you're 99% done.\n",
    "    \"\"\"\n",
    "    components = ['dynamic-depth-result', 'static-depth-result', 'memory']\n",
    "    bits = ['-A', '-B']\n",
    "    offsets = [0, 864]\n",
    "    for c in components:\n",
    "        curr_frame_off = 0\n",
    "        curr_memory_off = 0  \n",
    "        # No need for saved memory tracking since so far we're just stitching sequences with no decay.\n",
    "        \n",
    "        cum_df = None\n",
    "        print(\"\\n\\nStarting component: {}\".format(c))\n",
    "        \n",
    "        for bit, offset in zip(bits, offsets):\n",
    "            fk = 'frame_id' if c == 'memory' else 'frame'\n",
    "            fpath = os.path.join(root, base_tpl.format(bit, offset, c))\n",
    "            df = pd.read_csv(fpath)\n",
    "            \n",
    "            print(len(df))\n",
    "            print(\"Last:\", df[fk].iloc[-1])\n",
    "            \n",
    "            print(\"Adding {} to frame ids by key {}...\".format(curr_frame_off, fk))\n",
    "            df[fk] += curr_frame_off\n",
    "\n",
    "            if c == 'memory':\n",
    "                df['memory_usage_bytes'] += curr_memory_off\n",
    "            \n",
    "            if cum_df is None:\n",
    "                cum_df = df\n",
    "            else:\n",
    "                cum_df = pd.concat([cum_df, df])\n",
    "                \n",
    "            print(c, \"Len:\", len(cum_df))\n",
    "           \n",
    "            curr_frame_off += df[fk].iloc[-1] \n",
    "            if c == 'memory':\n",
    "                curr_memory_off = df['memory_usage_bytes'].iloc[-1]\n",
    "                print(\"Mem offset: \", curr_memory_off)\n",
    "        \n",
    "        out_fname = base_tpl.format(\"\", 0, c)\n",
    "        \n",
    "        out_fpath = os.path.join(root, out_fname)\n",
    "        cum_df.index = cum_df[fk]\n",
    "        del cum_df[fk]\n",
    "        \n",
    "        cum_df.to_csv(out_fpath)\n",
    "\n",
    "# stitch(\"k-0{}-kitti-odometry-09-offset-{}-depth-precomputed-dispnet-voxelsize-0.0500-max-depth-m-20.00-dynamic-mode-NO-direct-ref-NO-fusion-weights-{}.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc_fname_template = 'k-{}-kitti-odometry-09-offset-0-depth-precomputed-{}-'  \\\n",
    "                     'voxelsize-0.0500-max-depth-m-20.00-dynamic-mode-NO-direct-ref-' \\\n",
    "                     'NO-fusion-weights-static-depth-result.csv'\n",
    "mem_fname_template = 'k-{}-kitti-odometry-09-offset-0-depth-precomputed-{}-'  \\\n",
    "                     'voxelsize-0.0500-max-depth-m-20.00-dynamic-mode-NO-direct-ref-' \\\n",
    "                     'NO-fusion-weights-memory.csv'        \n",
    "\n",
    "ks = [0, 1, 2, 3, 5, 8, 10]\n",
    "depths = ['dispnet', 'elas']\n",
    "\n",
    "memory = {}\n",
    "frame_lim = 1000\n",
    "\n",
    "stats = {\n",
    "}\n",
    "\n",
    "for depth in depths:\n",
    "    memory[depth] = {}\n",
    "    stats[depth] = {\n",
    "        'k': [],\n",
    "        'accuracy': [],\n",
    "        'completeness': [],\n",
    "        'f1': [],\n",
    "        'mem-gb': [],\n",
    "    }\n",
    "    \n",
    "    for k in ks:\n",
    "        acc_fname = acc_fname_template.format(k, depth)\n",
    "        mem_fname = mem_fname_template.format(k, depth)\n",
    "        acc_fpath = os.path.join(root, acc_fname)\n",
    "        mem_fpath = os.path.join(root, mem_fname)\n",
    "        BYTE_TO_GB = 1.0 / (1024 * 1024 * 1024)\n",
    "        \n",
    "        df_acc = pd.read_csv(acc_fpath)\n",
    "        df_mem = pd.read_csv(mem_fpath)\n",
    "        mem_raw = df_mem['memory_usage_bytes'][:frame_lim]\n",
    "        memory[depth]['$\\Delta_\\\\textrm{{weight}} = {}$'.format(k)] = mem_raw * BYTE_TO_GB\n",
    "\n",
    "        total_gt = df_acc['fusion-total-3.00-kitti']\n",
    "        err = df_acc['fusion-error-3.00-kitti'] / (total_gt - df_acc['fusion-missing-3.00-kitti'])\n",
    "        completeness = (1.0 - df_acc['fusion-missing-separate-3.00-kitti'] / total_gt)\n",
    "        \n",
    "        err_m = err.mean()\n",
    "        acc_m = (1.0 - err).mean()\n",
    "        com_m = completeness.mean()\n",
    "        # Not super rigorous, but does combine the two metrics somewhat meaningfully...\n",
    "        poor_man_f1 = 2 * (acc_m * com_m) / (acc_m + com_m)\n",
    "        \n",
    "        stats[depth]['k'].append(k)\n",
    "        stats[depth]['accuracy'].append(acc_m)\n",
    "        stats[depth]['completeness'].append(com_m)\n",
    "        stats[depth]['f1'].append(poor_man_f1)\n",
    "        stats[depth]['mem-gb'].append(mem_raw[mem_raw.index[-1]] * BYTE_TO_GB)\n",
    "       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_elas = pd.DataFrame(memory['elas'])\n",
    "df_disp = pd.DataFrame(memory['dispnet'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Raw data preview (first 25 rows).\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 0$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 1$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 10$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 2$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 3$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 5$</th>\n",
       "      <th>$\\Delta_\\textrm{weight} = 8$</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "      <td>0.019814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.021767</td>\n",
       "      <td>0.021767</td>\n",
       "      <td>0.021767</td>\n",
       "      <td>0.021770</td>\n",
       "      <td>0.021767</td>\n",
       "      <td>0.021767</td>\n",
       "      <td>0.021767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.023651</td>\n",
       "      <td>0.023651</td>\n",
       "      <td>0.023643</td>\n",
       "      <td>0.023647</td>\n",
       "      <td>0.023647</td>\n",
       "      <td>0.023647</td>\n",
       "      <td>0.023647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.025314</td>\n",
       "      <td>0.025314</td>\n",
       "      <td>0.025314</td>\n",
       "      <td>0.025314</td>\n",
       "      <td>0.025311</td>\n",
       "      <td>0.025314</td>\n",
       "      <td>0.025314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.026978</td>\n",
       "      <td>0.026978</td>\n",
       "      <td>0.026974</td>\n",
       "      <td>0.026978</td>\n",
       "      <td>0.026974</td>\n",
       "      <td>0.026970</td>\n",
       "      <td>0.026978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.028355</td>\n",
       "      <td>0.028358</td>\n",
       "      <td>0.028355</td>\n",
       "      <td>0.028358</td>\n",
       "      <td>0.028347</td>\n",
       "      <td>0.028355</td>\n",
       "      <td>0.028358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.030071</td>\n",
       "      <td>0.030064</td>\n",
       "      <td>0.030071</td>\n",
       "      <td>0.030071</td>\n",
       "      <td>0.030067</td>\n",
       "      <td>0.030071</td>\n",
       "      <td>0.030071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.032024</td>\n",
       "      <td>0.032021</td>\n",
       "      <td>0.032024</td>\n",
       "      <td>0.032024</td>\n",
       "      <td>0.032021</td>\n",
       "      <td>0.032024</td>\n",
       "      <td>0.032024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.034290</td>\n",
       "      <td>0.034279</td>\n",
       "      <td>0.034283</td>\n",
       "      <td>0.034275</td>\n",
       "      <td>0.034286</td>\n",
       "      <td>0.034283</td>\n",
       "      <td>0.034283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.036377</td>\n",
       "      <td>0.036377</td>\n",
       "      <td>0.036381</td>\n",
       "      <td>0.036377</td>\n",
       "      <td>0.036373</td>\n",
       "      <td>0.036385</td>\n",
       "      <td>0.036373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.037815</td>\n",
       "      <td>0.037811</td>\n",
       "      <td>0.037819</td>\n",
       "      <td>0.037815</td>\n",
       "      <td>0.037807</td>\n",
       "      <td>0.037815</td>\n",
       "      <td>0.037811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.039536</td>\n",
       "      <td>0.039539</td>\n",
       "      <td>0.039543</td>\n",
       "      <td>0.039539</td>\n",
       "      <td>0.039539</td>\n",
       "      <td>0.039536</td>\n",
       "      <td>0.039543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.041405</td>\n",
       "      <td>0.041409</td>\n",
       "      <td>0.041412</td>\n",
       "      <td>0.041412</td>\n",
       "      <td>0.041409</td>\n",
       "      <td>0.041412</td>\n",
       "      <td>0.041409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.043381</td>\n",
       "      <td>0.043377</td>\n",
       "      <td>0.043381</td>\n",
       "      <td>0.043381</td>\n",
       "      <td>0.043377</td>\n",
       "      <td>0.043377</td>\n",
       "      <td>0.043381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.045097</td>\n",
       "      <td>0.045097</td>\n",
       "      <td>0.045097</td>\n",
       "      <td>0.045097</td>\n",
       "      <td>0.045094</td>\n",
       "      <td>0.045097</td>\n",
       "      <td>0.045097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.047234</td>\n",
       "      <td>0.047234</td>\n",
       "      <td>0.047234</td>\n",
       "      <td>0.047234</td>\n",
       "      <td>0.047230</td>\n",
       "      <td>0.047234</td>\n",
       "      <td>0.047234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.049091</td>\n",
       "      <td>0.049091</td>\n",
       "      <td>0.049091</td>\n",
       "      <td>0.049091</td>\n",
       "      <td>0.049088</td>\n",
       "      <td>0.049091</td>\n",
       "      <td>0.049091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.050426</td>\n",
       "      <td>0.050426</td>\n",
       "      <td>0.050426</td>\n",
       "      <td>0.050426</td>\n",
       "      <td>0.050423</td>\n",
       "      <td>0.050426</td>\n",
       "      <td>0.050426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.052738</td>\n",
       "      <td>0.052738</td>\n",
       "      <td>0.052738</td>\n",
       "      <td>0.052738</td>\n",
       "      <td>0.052734</td>\n",
       "      <td>0.052738</td>\n",
       "      <td>0.052738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.054771</td>\n",
       "      <td>0.054771</td>\n",
       "      <td>0.054771</td>\n",
       "      <td>0.054771</td>\n",
       "      <td>0.054768</td>\n",
       "      <td>0.054771</td>\n",
       "      <td>0.054771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.056915</td>\n",
       "      <td>0.056915</td>\n",
       "      <td>0.056915</td>\n",
       "      <td>0.056915</td>\n",
       "      <td>0.056911</td>\n",
       "      <td>0.056915</td>\n",
       "      <td>0.056915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.059120</td>\n",
       "      <td>0.059120</td>\n",
       "      <td>0.059120</td>\n",
       "      <td>0.059120</td>\n",
       "      <td>0.059116</td>\n",
       "      <td>0.059120</td>\n",
       "      <td>0.059120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.061340</td>\n",
       "      <td>0.061340</td>\n",
       "      <td>0.061340</td>\n",
       "      <td>0.061340</td>\n",
       "      <td>0.061337</td>\n",
       "      <td>0.061340</td>\n",
       "      <td>0.061340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.063980</td>\n",
       "      <td>0.063980</td>\n",
       "      <td>0.063980</td>\n",
       "      <td>0.063980</td>\n",
       "      <td>0.063976</td>\n",
       "      <td>0.063980</td>\n",
       "      <td>0.063980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    $\\Delta_\\textrm{weight} = 0$  $\\Delta_\\textrm{weight} = 1$  \\\n",
       "0                       0.000004                      0.000004   \n",
       "1                       0.019814                      0.019814   \n",
       "2                       0.021767                      0.021767   \n",
       "3                       0.023651                      0.023651   \n",
       "4                       0.025314                      0.025314   \n",
       "5                       0.026978                      0.026978   \n",
       "6                       0.028355                      0.028358   \n",
       "7                       0.030071                      0.030064   \n",
       "8                       0.032024                      0.032021   \n",
       "9                       0.034290                      0.034279   \n",
       "10                      0.036377                      0.036377   \n",
       "11                      0.037815                      0.037811   \n",
       "12                      0.039536                      0.039539   \n",
       "13                      0.041405                      0.041409   \n",
       "14                      0.043381                      0.043377   \n",
       "15                      0.045097                      0.045097   \n",
       "16                      0.047234                      0.047234   \n",
       "17                      0.049091                      0.049091   \n",
       "18                      0.050426                      0.050426   \n",
       "19                      0.052738                      0.052738   \n",
       "20                      0.054771                      0.054771   \n",
       "21                      0.056915                      0.056915   \n",
       "22                      0.059120                      0.059120   \n",
       "23                      0.061340                      0.061340   \n",
       "24                      0.063980                      0.063980   \n",
       "\n",
       "    $\\Delta_\\textrm{weight} = 10$  $\\Delta_\\textrm{weight} = 2$  \\\n",
       "0                        0.000004                      0.000004   \n",
       "1                        0.019814                      0.019814   \n",
       "2                        0.021767                      0.021770   \n",
       "3                        0.023643                      0.023647   \n",
       "4                        0.025314                      0.025314   \n",
       "5                        0.026974                      0.026978   \n",
       "6                        0.028355                      0.028358   \n",
       "7                        0.030071                      0.030071   \n",
       "8                        0.032024                      0.032024   \n",
       "9                        0.034283                      0.034275   \n",
       "10                       0.036381                      0.036377   \n",
       "11                       0.037819                      0.037815   \n",
       "12                       0.039543                      0.039539   \n",
       "13                       0.041412                      0.041412   \n",
       "14                       0.043381                      0.043381   \n",
       "15                       0.045097                      0.045097   \n",
       "16                       0.047234                      0.047234   \n",
       "17                       0.049091                      0.049091   \n",
       "18                       0.050426                      0.050426   \n",
       "19                       0.052738                      0.052738   \n",
       "20                       0.054771                      0.054771   \n",
       "21                       0.056915                      0.056915   \n",
       "22                       0.059120                      0.059120   \n",
       "23                       0.061340                      0.061340   \n",
       "24                       0.063980                      0.063980   \n",
       "\n",
       "    $\\Delta_\\textrm{weight} = 3$  $\\Delta_\\textrm{weight} = 5$  \\\n",
       "0                       0.000004                      0.000004   \n",
       "1                       0.019814                      0.019814   \n",
       "2                       0.021767                      0.021767   \n",
       "3                       0.023647                      0.023647   \n",
       "4                       0.025311                      0.025314   \n",
       "5                       0.026974                      0.026970   \n",
       "6                       0.028347                      0.028355   \n",
       "7                       0.030067                      0.030071   \n",
       "8                       0.032021                      0.032024   \n",
       "9                       0.034286                      0.034283   \n",
       "10                      0.036373                      0.036385   \n",
       "11                      0.037807                      0.037815   \n",
       "12                      0.039539                      0.039536   \n",
       "13                      0.041409                      0.041412   \n",
       "14                      0.043377                      0.043377   \n",
       "15                      0.045094                      0.045097   \n",
       "16                      0.047230                      0.047234   \n",
       "17                      0.049088                      0.049091   \n",
       "18                      0.050423                      0.050426   \n",
       "19                      0.052734                      0.052738   \n",
       "20                      0.054768                      0.054771   \n",
       "21                      0.056911                      0.056915   \n",
       "22                      0.059116                      0.059120   \n",
       "23                      0.061337                      0.061340   \n",
       "24                      0.063976                      0.063980   \n",
       "\n",
       "    $\\Delta_\\textrm{weight} = 8$  \n",
       "0                       0.000004  \n",
       "1                       0.019814  \n",
       "2                       0.021767  \n",
       "3                       0.023647  \n",
       "4                       0.025314  \n",
       "5                       0.026978  \n",
       "6                       0.028358  \n",
       "7                       0.030071  \n",
       "8                       0.032024  \n",
       "9                       0.034283  \n",
       "10                      0.036373  \n",
       "11                      0.037811  \n",
       "12                      0.039543  \n",
       "13                      0.041409  \n",
       "14                      0.043381  \n",
       "15                      0.045097  \n",
       "16                      0.047234  \n",
       "17                      0.049091  \n",
       "18                      0.050426  \n",
       "19                      0.052738  \n",
       "20                      0.054771  \n",
       "21                      0.056915  \n",
       "22                      0.059120  \n",
       "23                      0.061340  \n",
       "24                      0.063980  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preview_lim = 25\n",
    "print(\"Raw data preview (first {} rows).\".format(preview_lim))\n",
    "df_disp[:preview_lim]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/andreib/miniconda/envs/ds-ana/lib/python3.5/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3d29b4b978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set_plot_font_size(20)\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(6, 6), sharey=False)\n",
    "ylim = [0, 4.0]\n",
    "\n",
    "# This is dirty but does the job\n",
    "ordered_cols = ['$\\Delta_\\\\textrm{{weight}} = {}$'.format(i) for i in ks]\n",
    "\n",
    "\n",
    "df_disp.plot(y=ordered_cols, ax=ax1, legend=False)\n",
    "ax1.set_ylim(ylim)\n",
    "ax2.set_ylim(ylim)\n",
    "ax1.set_xlabel(\"Frame\")\n",
    "ax1.set_ylabel(\"GPU Memory usage (GiB)\")\n",
    "ax1.set_title(\"DispNet depth maps\")\n",
    "# ax1.legend(loc='upper left')\n",
    "ax1.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.75)\n",
    "\n",
    "df_elas.plot(y=ordered_cols, ax=ax2, legend=False)\n",
    "ax2.set_ylim(ylim)\n",
    "ax2.set_xlabel(\"Frame\")\n",
    "# ax2.set_ylabel(\"Memory usage (GiB)\")\n",
    "ax2.set_title(\"ELAS depth maps\")\n",
    "# ax2.legend(loc='upper left')\n",
    "ax2.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.75)\n",
    "\n",
    "for i in ks:\n",
    "    key = '$\\Delta_\\\\textrm{{weight}} = {}$'.format(i)\n",
    "    key_short = '$\\Delta_\\\\textrm{{w}} = {}$'.format(i)\n",
    "    ax1.text(df_disp.index[-1] + 20, df_disp[key].iloc[-1] - 0.10, key_short)\n",
    "    ax2.text(df_elas.index[-1] + 20, df_elas[key].iloc[-1] - 0.10, key_short)\n",
    "\n",
    "plt.subplots_adjust(left=-0.50, right=3.0)\n",
    "ax1.set_xlim((-50, 1000))\n",
    "ax2.set_xlim((-50, 1000))\n",
    "# fig.suptitle(\"Memory usage under varying voxel GC thresholds\")\n",
    "# plt.tight_layout()\n",
    "\n",
    "fig.savefig(os.path.join(fig_dir, 'recon-over-time.eps'), bbox_inches='tight')\n",
    "fig.savefig(os.path.join(fig_dir, 'recon-over-time.png'), bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABpoAAAGKCAYAAAAc65J7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3Xd8FHX+x/HX7KYnpJOQHhJ6h4QOggI2xN5OBTkLcv4sZ0XPU695Cp4dT8CugL2cqKiAGuk1FJEaWhIIECAhhBBS5vfHpGKAEJLdTfJ+Ph7z2M3M7ny/Q8h+d+Yzn8/XME0TERERERERERERERERkTNlc3YHREREREREREREREREpHFSoElERERERERERERERETqRIEmERERERERERERERERqRMFmkRERERERERERERERKROFGgSERERERERERERERGROlGgSUREREREREREREREROrEzdkdqA3DMMYBB03T/PQs3p8IpJU9Lq/rvkRERE6kcUpERFyVxigREREREWloLh9oMgzjYWAicM1ZvD/ENM0JVdZNNQwj2DTNafXUTRERaaY0TomIiKvSGCUiIiIiIo5gmKbp7D7UyDCMqUAwMBWYA1xzpnfOGYYRCGw3TTOopvVAa9M0c+qpyyIi0oxonBIREVelMUpERERERBzJZTOaTNO8o/y5YRh13c04YEUN+84xDGMbcC2gO/FEROSMaZwSERFXpTFKREREREQcyebsDjSwEcC2k2zbVrZdRETEWTROiYiIq9IYJSIiIiIitdLUA03JWJPW1uQg0MuBfRERETmRxikREXFVGqNERERERKRWmnqgKfAU23Kw6paLiIg4i8YpERFxVRqjRERERESkVpp6oOl0TnXyJCIi4mwap0RExFVpjBIREREREQDcnN2BhmIYxlmf+BiGMQ5rElx8fHyS2rRpc9b9qo3S0lJsNsfFAB3Zno6tcbbXVNtydHtN+djWrl2bbZpmS4c01kSc7TjlrDEK9HfTGNtydHs6tsbXlqPbc/SxaZw6MzqXcs32dGyNsz0dW+Nry9HtaYxyrtDQUDM+Pt5h7RUVFeHu7t7k2nJ0ezq2xtmejq3xtQWwcuXKWo1TTTbQZJpmjmEYZ7uPacA0gOTkZHPFihX10bXTyszMJCoqyiFtObo9HVvjbK+ptuXo9prysRmGsdMhDTUhZztOOWuMAv3dNMa2HN2ejq3xteXo9hx9bBqnzozOpVyzPR1b42xPx9b42nJ0exqjnCs+Ph6dSzW+9nRsjbM9HVvjawtqP04199J5IiIiIiIiIiIiIiIiUkdNPdCUA4ScZFsgsM2BfRERETmRxikREXFVGqNERERERKRWmnqgaS6QcJJtCWXbRUREnEXjlIiIuCqNUSIiIiIiUitNPdC0nFOfHK10YF9EREROpHFKRERclcYoERERERGplSYRaDIMI9AwjOE1bJoG9DIMI/CE1ycAwcDHjuifiIg0bxqnRETEVWmMEhERERGRs9WYAk3Bp9g2D5hz4gmSaZo5wARg4gmvnwhMKNsuIiJSHzROiYiIq9IYJSIiIiIiDcbN2R04GcMwHgZGUFmuYaphGNdgTUp7+wknNnM5yYS0pmlOMgxjnGEYE4E0IBH4yDTNTxv0AEREpEnTOCUiIq5KY5SIiIiIiDiSywaaTNOcBEyq5WsnYN1td7Lt0+qrXyIiItCMx6m8LEJnjYEbZ0KLcGf3RkREatBsxygREREREXGKxlQ6T0RERJwtZRIeWSsh5cRKSiIiIiIiIiIi0hwp0CQiIiK1k5cFq97DwITVMyBvr7N7JCIiIiIiIiIiTqZAk4iIiNTOz09DaZH1vLgQvr4XTNO5fRIREREREREREadSoElEREROLy8L1nxYZYUJm2bDawPg18+gpNhpXRMREREREREREedRoElEREROL2USmKXV1xl2yM2AT2+BV3rC0qlwPN85/RMREREREREREadQoElEREROL2MZlByvvs4sgcA4uG4GtIiA2Q/DC53hx6fgyH7n9FNERERERERERBzKzdkdEBERkUZg/IKKp5mZmURFRVXf3vES2LUEFr4MvzwLi16G7n+AAXdDSKKDOysiIiIiIiIiIo6iQJOIiIjUj9h+1pK9BRa9Aqtnwsp3rCDUgHshprezeygiIiIiIiIiIvVMpfNERETktKakpLEoLbvaukVp2UxJSfv9i0PbwqUvw5/XweD7Yfsv8OZweOtC2DQbSkt//x4REREREREREWmUFGgSERGR0+oWHcBdM1Mrgk2L0rK5a2Yq3aIDTv6mFuEw7Am47ze48BnIzYAProf/9oVV70FxoYN6LyIiIiIiIiIiDUWBJhERETmtAYmhTL6hJ+PeW8kLKRncNTOVyTf0ZEBi6Onf7OkH/f4E96TClW+Amyd8dTe82BXmPw8FOQ1/ACIiIiIiIiIi0iAUaBIREZFa6RUbRElpKZ+uzaZ7dAD9E0LObAd2d+h2DdwxH0Z/AWGdYN7f4YXO8N1fICe9YTouIiIiIiIiIiINRoEmERERqZVVuw7h6WYnwt+dnzbtZ9QrC8g4dPTMd2QYkHgejPnSCjq1vxiWToGXe8Dn4yBrnfW6vCxCZ42BvL31eyAiIiIiIiIiIlJvFGgSERGR0yqfk+m/N/XikzGduHVQPL/uPszw51KYsXQnpmnWbccR3eCq1+He1dBnHGz4GqYMgvevgFn34pG1ElIm1u/BiIiIiIiIiIhIvVGgSUSanSkpaSxKy662blFaNlNS0pzUIxHXtzYjt2JOJsMwePySzrx0XQ/CA7x47ItfGf3msrplN5ULjIULn4b718OwJ2D3Gtj8HQYmpL4HuZn1dzAiIiIiIiIiIlJvFGgSkWanW3QAd81MZcGWbEzTrMjU6BYd4Oyuibis8UMSGZAYWm3dZT2j+PnBofzr8i6k7jrEhS/OZ+bSXXXPbgLwDoLBD0DHUWDYrXUlRfBqH1j+JhQVnMVRiIiIiIiIiIhIfXNzdgdERABKSk2OFZVwqKAYI6eAY0UlHCsq5VhxCceKSigsKqWwuGxdkbXuWLH1vLC4tOL1hUUlZe+p4fVV1hUUFXPTm0vx97RTbMLLf+j5u4voInJ6hmFwU784hrRryYTP1vKXL9Yx+9c9PHNVN6ICveu207wsWPshmCWV647nwzf3w89PQ9/x0Ps28A6sn4MQEREREZEmwzCMOaZpjnB2P0REmhMFmkQakSkpaXSLDqgWEFmUls3ajFzGD0mst3ZKSs1qQZpdh46RaxzmWLEV8LEefx/0KawSGKoa9Klcf2LQp/I1RSV1z4DwsNvwdLPh6W7Hy92GV/mjm/UY6O2Ol7sdz/JtZetX7DjEsh0HAbjng1Su6BnFzQPiaRfeor7+KUWajZhgH2bc1pcZS3fx9LcbuOCFX3hsZEeu7x2DYRhntrOUSWCWVl9nd4c2w6G4EH78Jyx4EZLHQr//A/+IejsOERERERFpvAzDGA4Md3Y/RESaGwWaRBqRzpH+3Dl9FY9e3JEgWwGzt23jxblbuH1wa75Mzfxddk+1oE95wKdKxs/JsoFqDvpsrFUf3e0GXm52PN3teLrZqgR+Tgj6nBgYKgv+FOTn0So0uOL1nlW2ebrZf7c/Tzc7dtsZXsTGCtB9uDydsb3D+XzdAXrGBvLJygxmLN1F/4QQbh4Qx/CO4bjZVWFUpLZOzG569PN1fLuuDtlNGcug5Hj1dSXHITcdxi+APWtg4Uuw+FVYOhW6XQcD74XQtvV7QCIiIiIi0thMcHYHRESaIwWaRJzo6PFiDuYf52D+cQ7kH+fgEev5waPW8wP5xzmYX1jxmsPHigGY8Nnaavt5Ye6WGvfvZjOqBWTKgzRWAMhOgLd7ReaPZw2v8yp73dEjuUS0DK0xK6jq/rzc6xb0qSozM5OoqKiz2sfplM/JNPmGnsR5FXJ+j3jumpnKK3/oyfbsfN5fvJPx01cREeDFTf3iuK53DKF+ng3aJ5GmJCbYh+m39mXGsjpmN41fUPG0xs+EiO5w9Vtw3uOweDKkTreWjpfAwPsgOqmej0hERERERFydYRjjgKkoo0lExOEUaBKpJ6Zpknu0iANVAkMVAaQalgP5hRwrKq1xX242g2Bfj4qlS1QAIb4eBPt6EuzrzsK0A3z3axZX9Izipn5x1bN83CqDP/WVjWNd6G06panWZuQy+QZrTqbMzEwGJIYy+YaeFSUIbx+cwI8b9/He4h08+/0mXpq7hUu6RTBmQDw9YjQnjEht2GwGo/vFMfRss5tOJbg1jHwOhjwCS6fA8tdhwyyIHwyD/gyJw+BMy/aJiIiIiEijYxhGIHAQyHF2X0REmiMFmqTJqa95jIpLSjl0tKgiKHQw/ziHqgSOyjOQDh2tzDwqqTluhLe7nWBfD0L8rKVtuB/BPh4E+3lUCSBVBpb8vdxOetf/orRsXpi7hbG9w/nqt/1ckxxNUlzQGf0bNXc1/T8YkBha8X/GbjMY0SmcEZ3C2brvCO8v3sGnKzP4PDWT7tEBjOkfz8huEXi52x3cc5HG56yzm2rDryUMe9wKLq18xyqpN/0qaNUVBv4ZOl0Odn3lERFpqhw1j6mIiLi0caZpTiqbo0lERBxMV12kyekWHVClLFplmbTnr+1OZk5BlWBRIQfKStUdOnq84nl5ECm3oOikbQR4uxPi60GQrwcxwT70iAnEvbSQuFYhFcGiEF9Pgv08CPbxwNujfgISJyv5Vp6dI/WvTZgff7+sCw9e0J4vUjN5d9EOHvhkDf/+dgPX94nhxr5xRNZXdoZIE1U1u+nhTxsouwnAswUMuBv6jIO1H1vzOH12K/z4T2t9jxvBXX+vIiJNzcm+/0++oaezuyYiIg5gGEYvYJWz+yEi0pwp0CSNnmma7D9SSOahAjIOFZCZU0BSbBA3v7WMAE87BwuKcbfbGPv28hrfb7cZBPmUZxZ50DHS38o2KstAqpppFOzrQZCPB+41lKRzxNxCpyr5pkBTw2rh5c6Y/vGM7hfHorQDvLtoB6/9nMZrP6dxfqdWjBkQR/+EkPrL0BBpgmKCfZhxW/Xspr+O7Mh19ZndBODmCb1GW4GlTd/Cghfgmwfg52eg7x3Q+zbwViaoiEhTUf6d+In35/Gqx8s8fvweJo8epu/HIiLNx3DTNCc5uxMiIs2ZAk3S4M62lEVxSSlZh4+RWRZEKn8sDypl5hRwvLh6zboAb3cCvN3JPnKc9q1aMKhNaFmWkZWFFFIl66iFlxs2W+MIDpyu5Js0PMMwGNgmlIFtQsk4dJTpS3bx0fJdfLc+i3bhfozpH88VPaPw9dTHq0hNTsxueuTzdXzTENlNVmPQ8RLoMBJ2LrQCTj/+Cxa8CEljof//gX9k/bYpIiJOMSAxlEf9ZtE2bz03l3zMAx+H0j06kO4xgXSPCaBbdCB++n4mItLkGIZxNfDpGb5nHDAOICoqiszMzIboWo3y8/Md1p4j23J0ezq2xtmejq3xtXUm9E1bGtzpSlkUFpewO6c8kHTUCiAdKiCjLKiUdfgYJaVmtX2G+nkSFeRNpwh/zu8UTlSQN1GB3hWP6zJzuWtmatk8RocY1jFMwRipd9FBPjxyUQf+PLwts9bs5t3FO/jrl78ycfZGrk6OZnS/OBJa+jm7myIuqSK7aelOnp69seGymwAMA+IHWUvWOquk3pL/wtKp0P06GHAvtGwHeVmEzhoDN86EFuH12wcREWlQy9f9xuAjs7EZJjfYf6LIqyOLM1vz8vpACvDCMKBtmF9F8KlHTCDtW7WosVKBiIg0KsGmaW47kzeYpjkNmAaQnJxsNnR1mqocUQ3HGW05uj0dW+NsT8fW+No6Ewo0SYPrHh3IIxd1YNx7K+kS7s3qPfn0iAnk2e83kXFoNfvzCqu93mZAK38vooN86NM6uFoAKTrIm8hAb7zcTz7nkeYxEkfzcrdzTXIMVydFk5qew3uLdjB9yU7eXriDc9q15Ob+cQxtH+bsboq4HJvNYHT/eIa2D+OhT9fwyOfr+PbXLJ65smvDzX3Wqitc9Qac91dYNBlS34fUGVbWEwYeWSshZSJc8nzDtC8iIvVuUVo2GZ89SZJhggl2o4Rbc1/hVgAvOOYTyV6PWDaXtGLFb6F8kxrOy6WR5LoF0yUqsCz4FEDPmCBigr1VCllEpJEwDGNcWdBIREScTIEmOWt5x4oqs5AOHa0oa1de2u5g/vGK1y7ZlYfNgKzcY0QFeXNu+5ZEBfoQHVQZTGoV4HVWdxZqHiNxFsMw6BUbRK/YIB4b2YkPlu1ixtKd3PruCmKCvbm0YxC3B7Uk0MfD2V0VcSkxwT7MvK1fRXbT0Gd/ZuyAOB69uGPFa86k5GqtBMXDyP/AkAmwbCosnQKFeRgAqdOt9cpqEhFpFLambeVGewq2khIADKDU5sEvbR5maBR4ZW8mLnszcdlzGGHmQ9lXsUKbD+kHoli/J5zNSyL5zoxgv2csQTEd6BQTRo8YK/sp2Lf6d7eK0uBhxRWZsIv22et3nBIRkVMyDCMBOOjsfoiIiEWBpmaqtvMmmabJ4YJi0qsEkMoDSuWBpNyComr79nSzER3kTXSQD12jA4gO8uZoYTHvLd7Jhe2DmLsll39f2bXBgj6ax0hcQcsWntwzrC1/GprID+v38u7iHby6cDdvLM3i8h5RjBkQR+fIAGd3U8RllGc3DWkXxh3TVzBt/naWbD/I34ZHsfOEkqv1yq+lld2UlwWrZ4JZAiWF8PZFMPpzKyAlIiIubczxj4HqpbZtBgz13wNDqmSomibk7YHszZC9Bc/szbTJ3kJi9maMwwvKXgMlu2yk72xJWmkkn5kRHPKJxyO8A6HxnemY2JoOrVpw18xUvkn8glZZK9kz6+/clXZFw4xTIiJyMsOBEYZhXHfC+kAAwzA+Kft5qmmacx3aMxGRZkiBpmaqYt6kP/QkgGJ+WrKDZ2Zv4rIekTz5v1+rBZXyCourvdfHw14RSEqKC6rIRooOsjKTQnw9qpWbKC9lN2V0EnFehVzeJ0Gl7MQ1OGA+Fne7jZHdIhjZLYKUNVv5Lq2AL1Iz+GhFOr3jgxjTP54Lu7TS/AAiZWJDfPjm7sH84+vfeGfRDq59LxcPNzuvj05uuDEjLwvWfWIFmcodTIOXk6DP7XDOg+Cr8UpExGVlLIOS49XXlRy31ldlGOAfaS0JQytXAxzPhwNbIXsL9uzNRO3bRMusTQzJnYfb8UJIB9Ih5xdftpmRPOseTuimxRiGSfDmj5l65Z/orXMbERGHqTrPUlWGYVwNDDdN8xrH90pEpPlSoKmZyT1aRGr6IVJ35RAd5M2Nbyytdu/fjKW7aOHpVhE46pcQYgWSAisDSYE+7mdUt1yl7BqAJqyvHymTHDofS5tQb57u3oZHLuzAJyvTeW/xTu7+IJWwFp7c0DeWG/rEEubv1eD9EHF1NpvB3y7tjGmavLt4J8XHS3huziZCW3jSvlWL+m8wZRKYpdXX2d0hKMEqq5c6HQbeA/3uBE+/+m9fRETOzvgFFU/rPDmyhy9EdLcWwL1sobQUctMhewt5mb+Rl/4bofs30enwctwN6wYFT4ro9flg9n0bjxnSjsC4zniGd4CW7SCkrcYOEREREWnyFGhqwopLStm890hFYGnVrkNs258PWKUk2oW3oFOkP+t3H2Zk1wjuPDeR6CAfArzd67UfKmXXABwVIDFN6+JrcSEUHoHSIigtgZKisufFUFJsPVb7uTbbyvZVWlT23Hpti9xD8JtXxc9Vt/3u51ptq9rnKttKisAstu5gXfkOxPaDjpeCe8MHegJ83LltcAK3DGxNyub9vLt4By/O3cLkH7dyUdcIxg6Io1dskCailmZtUVo2s9buYWzvcD5Zm83mvXmMfHk+44ckctd5bfByt9dfYzXeCV8Ebh5w5xKY9w/46SlY9joMnQC9brYCUSIi0vTZbBAUB0FxtGg7nBYAeVmUvNgNqiTCmtjYWOBPVPpaQjLmgFF5A4PpH4UR2g5atofQthDaHkLbgV+YlWUlIiL1KdjZHRARaY4UaGpC9ucVsjrdCiil7jrE2oxcjh63zn5CfD3oGRvIVb2i6RkbSLfoQNZm5HDXzFTG9g7nq98OcGO/WDpH6sKZSzFNKDgER/ZB/j7r8UAarHoHA9MKkBQXgM29xqBN3QIzVX+25t+qwz2hddbCsIHNzTomu1vlc5tb9Z9/t80d3H0qn9vsZa+r8rzqtm0psHe9VSrLLIHPbwf3e6H1EGh3PrS9AAIa9shtNoNzO4RxbocwtmfnM33JTj5ekc6sNbvpHOnPzf3jubRHZP1eUBdpBBZVmZMpzquQ83vEc+eMVfSPDWLyT1v5Zt0enrqiS/3dsHC6O+GvnwHpy2DOk/DNA7D4VTjvceh8hS4Qiog0Q3tm/YOQkhKqfkMrxSCxXRfS+/+TWZv3sH3LOo5nbSKBTNrl7KZrQQYxO5bgXlpQ+SavACvgFFoWgGpZFoAKjLO+61aligYiIqdUVjLvDiC57Oc0YBUwwTTNbc7sm4hIc6BAUyN1vLiUDXsOlwWVckhNP0T6Qeukxc1m0CnSn2uTY+gZG0jPmCBigr1rnDep6kU8zZvkIDUFjyqe74cjeyuf5++vCPbUvK8SWPcZeAeWBVLsZYEUtxN+Llvn7l2nIE5u/lECAkNOEsRxq1xOu+30fdy9Z0/dyp2cibwsKzOh6nwsdg/ofCXsmA+bZ1vrwrtWBp2ik62+NpDWob48fkknHji/HV+m7ubdRTt4+LO1/Hv2Bq5LjuGmfnHEBPs0WPsirqSmkqv/vbEXazNyueOcRB77ch03vL6Ua5Ki+cvFHQny9Wj4TsX0gT9+C1t+gLl/g0//CItehuF/h4QhDd++iIi4DPfdK/Cg+jy2HhTjuWcF/RJC6JcQAhd24UhhMcu2H2Dh1gO8tjWbjVmHieAgXb32cm7IIXp67yO2NAPvrXMwVk+v3JndA4ITrdJ75YGoDbMcWvJZRKSxMU3zU+BTZ/dDRKS5ahSBJsMwxgGJQFrZ4/KyAeRM93M1MKLKqjl12U9DmJKSRrfogGpBnkVp2azNyGX8kER25xRYAaVdh0hNz2FdZi7Hi61yDK38vegVF8iYfvH0jA2kS1TAaTMgNG9SPSstxXbsEOw7XBY02l8WQNpb+bw8qJS/38oYOpHNDXzDwK+l9RjexSqn4RtW9tgSDDvMuNIqZVfOMOCO+Q16Z+ORzEwCGjr440g1zccC4OYJ966B/Ztgy/ew+QdY8CLMfw68g6HtCGh7PrQZBt5BDdI1Hw83bugbyx/6xLB0+0HeW7yDNxZsZ9r8bQzrEMbNA+IZmBiKzaYsClfSHMYpRzpdydXv/3wOL83bwrRftvHjxn08MaoTl3aPbPhyk4YB7S6ANsNh7Ufw41Pw3qWQOAyG/w0iujVs+yIidaAxqv6FPris4nnVTNgTz6L8PN04r0M453WwvqdnHylkUdoBFm3N5r9p2aRnWjcKhrXwZFhbD4aFHSbJZx9BR3fA/s2Q9Sulv83ChvW91QBY8RbZ+7PY4NmVwUPOt84Z3Dwb+IhFRKReKDtVRJowlw80GYbxMBBimuaEKuumGoYRbJrmtDPYz1QA0zTvqLJujmEYuMIJUrfogIqMolZupby9cDuTvt9E10h/3lm4g6zDxwDwcLPRLSqAm/vH0TM2iJ6xgUQEeJ9xe81i3qSzHcBLS63Mo99lHZUHkvZWPs/fT0SNwSN3K0DkFwZ+4VaGTHkgyS+seiDJK9CqAX8qX99vZURVZZbqzsYzVeN8LMet9YYBYR2sZeC9UJADafOsoNPWOdbFZcNuzenU9nzronPLDvVePsswjIo7YvfkFjBz6S4+WLaLuW8uI6GlL2P6xXFVUjQtvFTu0tmayzjlSrzc7Uy4sAOXdo/kkc/Xce+Hq/lsVSZPXd7FMZl/Njv0uMHKglz+Bsz/D0wdDF2vhfMeg6D4hu+DiEgtaIxyLaF+nlzaPZJLu0cCkH7wKAu3ZrMw7QA/bM3mg3UGEE7r0AQGJF7DwHNDcTeLKPl8POcbS7CZJZiA384fGMw3sPkZK/spvDNE9oKoXtZjy/YNmokvIiJ1NOdJZaeKSJPl0oEmwzACgUdN0zwxdWACsN0wjI9N08ypxX6GA+NM0zzxSvAEYB4ukFpbnlF027srKDhunUAAZB0upG9CMD1jAukVF0SHVv54uJ0mGCGWlEm/H8BLS6HgYPVSdfllmUcVz8uWo9knyTxyr8wwatHKuoPdN4ycEk8CI9tYAaXy7d5B9RuAOFWARGrvdPOxVOUdCF2uspbSEshcCZu/tzKe5j5pLYGxVnm9dhdA/GBw96rX7kYEePPA+e2567w2zF6XxbuLd/C3Wb/x7PebuLJXNGP6x9E2vEW9tim105zGKVfUMcKfz/80gOlLdjLpu42MeCGF+0e045aBrXGzO2CsdPeCAXdBz5tg4Uuw5DVY/wX0vhXOeQh8m9DNGyLS6GiMcn0xwT5c3yeW6/vEUlpqsmlvHgu3ZrMo7QBfpmYyY+kuwoxDzPdcjq2s5LOBibvdDrf8ADm7YPcqyFwFaz+GFW9aO3b3hYjuZYGnntYSnKB5BUVEnCk3E9Z+aGWnrp4BQyYoq0lEmhSXDjQB44AVJ640TTPHMIxtwLVAbe7Em0gNJ0Cmaa4yDAPDMK52hTvxBiSGckm3CD5ekcEl3SL426WdCfVTGYRaO5YLuRmQkw5718OqdzAwYeXbsHOhlZmSv7/6vDzlbO5lAaKW0CKiInhUsa5qBpJXYI0nafmZmQQ2dHm5MwmQSP2z2a15WmL6wLDHrS+KW36wltUzYPnr4OYNCUMr53YKqL/fkaebnct7RnF5zyjWZuTw7qKdfLQinfeX7GRAYghj+sezbf8ResQGnrQMp9S7ZjVOuSK7zeDmAfGM6BTOE/9bz7+/3ciXqbt55qqudIsOdEwnvANh+JPQZxykPGPNAZc6AwbeA/3uBE8/x/RDRKQ6jVGNiM1m0DHCn44R/tw2OIGiklLWZuTg/t1D2PZUL/lcWlLM9h+mEnTNy4R0vrxsZSkc2FoZeNq9yhqPSspKbnsFWgGn8qynqF7gH3lkescKAAAgAElEQVTyDqm8k4hI/Zr/nFUdxSyxFmU1iUgT4+qBphHAtpNs21a2vTYnR72o4SSrzArgOlzgTrxFadnM3bCPsb3D+eq3A2zem9e0Ak1nc7JSUgxHsioDSbnp1vPcjMrnhYdrfq9pwvF8a36dilJ1La0gUvnzkwSPRE4pIAqS/2gtRcdgx4KyuZ2+h82zrdeEd60MOhkR9dZ0t+hAnrs2kL9c3IGPVqQzffFOxk9fSYivO0ePl/LCdd3pGmR9rpSX5ZQG0azGKVcWGejN62OS+H59Fk/8bz2Xv7qQsQNa88D57fD1dNDXHf8IGPUS9Ps/+PEf8NNT1kW+IQ9D0liwq9SliDiUxqhGzN1uIykuGMxNQPUqC+4UU7h9MclPzSUpNohhHcMZ3jGMNmFtMVq2g+7XWy8sKYJ9v1UGnjJTrflHy2+882tVJfDU03r0Cba21VQdQkRE6iYvy7o5tfzzt6RIWU0i0uS4eqApGZhzkm0HgeFnsK+TlYXIwTp5cqqqF4PjvAo5v0d8xc9NZt6kU52sFOZVBo5ydlUJIpUFkg7v/n0mkncQBMRAUGurXFlANATGgLsPfDS68u49TCuT6bzHNYBLw3H3grbDreWiSZC9GTZ/Z83ttOBFmP8crTwDof0F1txObYZZ/4fPUoifJ3cObcO4wQnM27iP9xbvYOHWA4yfvooekb7syi1qWp8jrqfZjFONgWEYXNglggFtQpn03UbeWrid79dn8c/LO1dMxO4QLdvBddMhfblVXvPbB2HJf61xqPMVurFBRBxFY1QTsGjEl9XOE3ce8+Sumak8cGE77skrZO6GvUz8biMTv9tIXIgPwzqEM7xTGL3jg3G3u1sl9CK6A3+0dnj8KOz9tUrwaRVs+raywaB4aNkRts6xqkPoQqiIyNlLmWTNr12V5tsWkSbG1QNNp6p5kwME13I/OafYVyCQcCadaghrM3IrLgZnZmZWzNm0NiO38V8gLi21TmZS37dOVla9C8XH4OjBskDSLqvsXVU2N6uUQ0AMxA20gkjlgaSAGPCPOnkpoq/vh4pZrspoABdHMgxrEuaW7WHgvVbZxrR5FK7+Ep+tc2HtR1bKfExfa16ndhdAyw5ndfHZzW7jgs6tuKBzK7bszeOBj9ewOjOXe85r0/g/Q1xbsxmnGhN/L3f+dXlXLu8RxaOfr+OWd1YwslsET47qRFiL+p1D7ZRiesPYb2DLHJj7N/j0j7DoZRj+d2jZXiWJRKShaYxqAk51nnjfiHbcN6Ide3ILmLdhH3M37GX60p28tXA7LbzcGNo+jOEdwxjaLowAn7KsWg+fylLQ5Y7lwu7VlYGntHmVc9UWH4M3R8CAu63y0CFtdMOEiMiZ0nzbItIMuHqg6XRqO/nCCk5+AuQSJ0Y1zZ0yIDG0cVwgLi2BvD1WSbucXVbgKGdXlZ8zqmQXYZ20rPsEQttZQaPYfpWBpIAYK5jkF27Nh1MXGsDF1XgHQperOBTUD5+IVtYJ/ObvrDJ7c5+0loDYyqBT/CBw965zc/uPFJKRU8DY3uFMX7qLfokhjeOzpGlqMuNUY5QcH8w39wxmakoar/y4lfmb9/PoxR25LjkGm81BF8kMwyqf2WaYNVH7T0/Be5eCfyQeh/foJggRcSaNUY1Abc4TIwK8ualfHDf1iyO/sJj5W7KZt2EvP27cx6w1u7HbDPrEBzOsYxjDO4YTH+pbfYdeAZAwxFrysuCl7tW35+yysnMBWkRaAaeEIdB6iFU2VkRETq3qfNvpu4j6dCQEx8PNs5zXJxGReuaygSbDMOpzBu8JwMoa2ujFyctAYBjGOKxJdImKiiIzM7Meu3Ry+fn5DmvLdnQ/QT/8mT3nv0ipT8uaX1RahD1/H/a8TNyOZGLP2439SCZueXuwH8nEfiQLw6xeN7zEO4QSv0iKA9tSGt4b302fYpRWvqYUg73DX625zTzTOsGpq1EfVTzNz8/H17fKiVQD/rs68vfm6PaaaluObi8/P5/MPVlgi4QOt0CHW7AdycIr/Re80lPwTJ2ObfnrlNq9KIzqx7HYIRyLGUKpX6tat7EyI48nZu/gHxfF0yHIRq9oP+58fwX/uCiepOgWDXh0zY+zxylnjVHQ+D4TruzgQ1J4O579KZ1HP1/Hh0u2MeHcGOKCf5/d1KDH1vIcuLIvfmvewH/VqxiAufId9sVdSnFw24Zps4rG9ntz1faaaluObs/Rx9bcOHuMKtve5M+lHN1ebdvqGgRdB4Ryd78QNuw9yoLtuSzYfph/fbOBf32zgfggTwa2DmBQa386t/LFXuXmi4AF/8C3tISqt2OYNjeOtr6A4xHJeGYuxnPjt9jXzASgKDCRwqh+FEb1pzCiN6ZH3b5v6vfWONtrqm05oz1pRmx2SLoZfvwnZG+B0IY/DxARcQSXDTSZpplj1FNKvmmaqwzDmGAYxlTTNO+AipOvZKyJcGusK26a5jTKJshNTk42o6Ki6qU/p5OZmYmj2uLr5zD3r8Zn7WTocaM1H1K1bKR0OJx5Qi1ZA1pEWJlH8f3LspBirZ8D4yAgGru7N3bAA6xSdoatWrM2TCI2vdfgd3E78t/Sob83B7fXVNtydHs1txUF7ZOA+6DoGOxcgG3z93hv/h7vBT9bLwnvYmU6tb0AopNPme03a2sa/x2dXFFe5dJ2UYSGhrI2I5dLHfjv2hw4e5xy1hgFrvB3c+aiouDzzgl8siKDp77dwNgPN3PnuYn8aWginm6Vf1MOObZ1x8DuASXHMcwSwr+4Bs7/B/S+DezuDdZsY/y9uWJ7TbUtR7fn6GNrbpw9RpW9r+mfSzm4vbq0FRsDFyRbz3cdOMrcDXuZt3EvH63ez4xV+wj29WBo+5aM6BjO4HYtOZaeil9pUbV9GKVFFOzdQujoGcB9ZaXR18G2n3HfloL7ps/xWz/DKg0d1cvKdEoYapXnc/NssGM7G67+e2ss7TXVtpzRnjQzvcbAz8/Airfgwqed3RsRkXrhsoGm+maa5iTDMHqV3Vl3EMgxTXOaYRh3YJ0gNT2mCQWHrOygvN3W4+E9lc8P7YR966271dZ9Yi1gBYX8y+ZDih90QiAp1pofqZYnDIBK2YnUlrsXtBluLRdNguzNVom9zT/Aghdh/nPgHWxtb3eBVYrLO6jaLhp1Gc5mrlmOUw5mGAbX9o7h3A5h/PPr33hx7hZmrdlNv4QQRnaLqPZ3sigtm7UZuTX+TZ2VvCxrYvWq46JZDN89AivfgQufgcRz67dNEZGzpDGqaYgN8eGWQa25ZVBrDh8rImXTfuZt2Mu8Dfv4fFUmHnYbHSKeZ+vhIzxzVTeSQk12HvPkrpmpTL6iJxWjpM0GEd2tZeC9UFwIGcth28+wLQUWvADz/wNu3hDXvzLw1Kqb9V4RkebOLww6jrLOC8573Jo/T0SkkXP1QFMOEHKSbYGc4UmNaZqrgFU17OfEdc6Tl1W7ycGLjlnzIpUvh2t6ngXFBb9/r3cw+Edak74aNitbybBDuwutOyn8I+v3juqqtWh1V5BI7RgGtGxvLQPvhYIcSPsRNn8PW+fAuo+tv9uYvtb8L+0uhJYdKidnru1niZyt5jdONQEtW3jy8h96ckWvKP76xa/MWLqLT1dmMPmGXnQKsIJMd81MZfINPeu/8ZRJJ2QJAzY36yLcgS3w/uXQ4RK44CkIiq//9kWkOdEYJSfl7+XOqO6RjOoeSXFJKSt2HmLehr3M3bCPo8dLuOeDVEJ93DhabPLs1d1OfdOSm6d1g2L8IDjvr9Z55o6FsD3FCj7NfdJ6nXcQtD7HCjq1HgLBCZXfXUVEmpvet8L6z62l503O7o2IyFlz9UDTXE498ezcemgjAavuuGv4eSIeWSth9kPQ/Q9weHdlRtLhPZXPCw79/r1u3tZkrC0iICqp8nn54h8Bfq2srInySV7LL3aZJZA2D9y8GrRsj4jUkXcgdLnSWkpLIHOVle205XuY+zdrCYitDDptmGV9lqRMbPASlc1c8xunmpBz24cx5/5zeGHOZt6Yv51x769gaEIAa7IKmHxDz4bJBDxZlu+RLLhzKSx5FX55Dib3gYH3wKD7wMO35n2JiJyaxiipFTe7jX4JIfRLCOGxkZ1I23+Ex7/8lUVpBwC464NU3lu8k1HdI7moSytC/E5T3cIrADpcbC1gncdu/6Uy8PTb/6z1AbGQcA4knIvNqy2gGxJFpBmJG2jdLLr8TQWaRKRJcPVA03LgupNsSwA+qc1OyiaqTS6rE151/dVYZR8+Pate1pe8LEh9DwPT+vJd/gXcsIFvmBUoCoqH2H5lQaRIaNHKykBq0Qq8Amt/R1hNd1SbpbooLdIY2OwQ09tahj1uBaS3/GBlO62eCcvfALDKYq6eAUMmKKup4TSvcaoJ8vFw47GRnbisRxR/fHsZP6Xl0i7cj04R/g3T4OmyfAc/YN1oMudJ+OVZ6296xD+gy1W661tEzpTGKKmTvYePsTErj7G9w/ni14OM6BhOavoh/vrlrzz51XoGtQllVPdILugcTguvWtyk6B8B3a+zFtOEA1vLyuz9DBtmQep0IgDCOlvZTglDIG4AeLZoyMMUEXEuw4DkW2D2w7A7FSIboJqCiIgDuXqgaRow0TCMQNM0c8pXGoaRAAQDH1d9cfmktKZpnnh33h3AuLL9VfUornQHXsokyi4NW2V02o+Ei56xgkz2ev5Vad4kkabDPxKSxlpL0TH4eIxVXs8sVQC54TWvcaoJO3ysiOJSkx5RvqzOPMKQZ3/m+Wu7M6yjE4K0/pFw1etWOY3ZD8Nnt1p3Ol40ESK6Ob4/ItJYaYySM1a1fGycVyHn94i3fv5DTwJ9PPhqzW5mrdnNg5+s4S9f2DivfRijukcyrGMYXu720zdgGBDa1lr63G5l6u9ZTe7qWQRkr7JumFryqnU+HJVcGXiKSgY3j4Y+fBERx+p+vVWdZPmbcNlkZ/dGROSsuHSgyTTNHMMwJgATsU5wyk0EJlQ9YSozD+hlGMaIE06Q5gArq77QMIypwIoT78xzmvLJwUuLrJ9Li62SWBc/W/9BJtC8SSJN1bEcqyxJecZiyXFlNTWgZjVONWHlF9VevbEXcV6FpGQU8/iX67n13RVc1SuaJ0Z1IsDbCWVlY/vB7T9B6vsw7x8wbYgVUD73r+B7smlXREQsGqOkLtZm5FaUj83MzGRAYiiTb+jJ2oxcxg9JpFOkPxMubM+qXTnMWrObr9fu4bv1Wfh62BnRKZxLe0QyqE1LPNxstWvQZoeoJI7QioCoKCgqgPSlZRlPKdYNUynPgLuvleWUMNQKPIV1Blst2xARcVVeAdD1alj7CZz/L6tkvohII+XSgSYA0zQnGYYxzjCMiUAakAh8dJISDXOpYWJb0zQ/NQzj4bITouCy13ziUidGKmUnIvVBnyUO12zGqSbsxItqN/SNIzrIhyk/p/Hl6kwWbs3mmau6MrR9mOM7Z7NbwaVOl8HPE2HZNPj1czj3MavURkPcjCIiTYbGKDlT44ck/m7dgMTQavMWGoZBUlwQSXFBPH5JJ5ZuO8BXa3Yz+9csvly9m0Afdy7q0opR3SPp2zoEu+0MSr+6e5cFk4ZaPxccgh0LKgNPPzxmrfcJhdbnVL42KK4ORysi9cUwjHjgaqxxJhlrrCgfM3KAg2WP27BKu841TXO1M/rqcpJvhVXvwZoPod94Z/dGRKTOGsXVidqexJimOYGTlG8wTXNSvXaqvqmUnYjUB32WOEWzGKeasJouqp3TriXntGvJmvQcHvhkDWPfXs4f+sTwl4s71m4+ivrmHWSV000aC99NgNkPwcq3rXJ6rc9xfH9EpNHQGCUNyW4zGNAmlAFtQvnHZV2Yv2U/s9bs5n+rd/PBsnTCWngyslsEo7pH0jMmEONM5xv0DoKOo6wFIDfTyt4vDzyt/9xaHxRvBZxaD7EWZf6KNDjDMPyxSqvegTX334l/4DlAbtn68i/cScA1gGkYxjas+QKnmaa5wxF9dkmRPSAqCVa8BX3v0LysItJoNYpAU7OgUnYiUh/0WSJSr7rHBPL13YN4Ye5mXv9lG79szmbS1d0Y2Cb09G9uCGEdYPSXsPEb+P5ReHeUle10/r8gMNY5fRIREQE83GwM6xjOsI7hFBwvYd7Gvcxas5sZS3fx9sIdRAd5M6p7JJd2j6RDqxZnHnQCCIiCHjdYi2nC/k1W0Gl7Cqz7DFa+Y72uVdfKbKfY/uDhW7mPvCxCZ42BG2eqtLRIHRmG8SBWKVYDK0vpWaxMpVWmaW4/xftaA72A3sBw4BFggmEYE03T/EuDd9xVJd8K/7vTyuBsPdjZvRERqRMFmkREREROwcvdzqMXdeT8Tq146JM13PjGUkb3i+ORizrg6+mEr1KGAR0vgTbDYNFkWPA8bP4eBv4ZBt4LHj6O75OIiEgV3h52LukWySXdIjl8rIgf1u/lqzW7mfbLNl77OY02YX5c2j2SUd0jaR3qe/od1sQwrBswwjpY5aZKimF3amXgaelUWPQK2Nwhpq81t1PCUFg9E4+slSotLVIHZVlMP2IFi6YBU03TTK3t+8uCUNuBz8r21xoYD4w3DGMckGSa5s5677ir63IlfP8XWPGmAk0i0mgp0CQiIiJSC0lxQXx772Ce/X4Tby3cTsrm/Tx7dTf6JjipPI+7Nwx5CHr8AeY8YU2WvnoGnP9P6HS5ym6IiIhL8Pdy5+qkaK5OiubAkUK+/TWLWWt28/yczTw/ZzNdowI4J96XG32DiQz0rntDdjeI6W0tQx6C40dh1+KyMns/w0//hp+eAsrqe62eDkMmKKtJ5Mz8WPaYeKrMpdoq28cEwzCexiqjtw2wn+1+Gx13b+hxIyybCnl79bkkIo2SzdkdEBEREWksvNztPH5JJz4a1x/DgOtfX8LfZ62n4HiJ8zoVEA1XvwVjvwWvQPhkrFVSb+965/VJRESkBiF+nozuF8fHd/Rn8aPn8deRHTEMeHXhbgY88yPXTFnE+4t3cOBI4dk35uFjZf+e/08YPx8eSoOEc6m4DFJcCO+MhP2bz74tkeZjqmmayfURZKrKNM0c0zRHYGU3NU/Jt0BpMaS+5+yeiIjUiQJNIiIiImeoT+tgZt87mDH94nh74Q4ufnk+K3cedG6n4gfCHSkw8nkryDRlEHzzIBx1cr9ERERqEBHgzW2DE/jqrkF8NLojD4xoR87RIh7/33r6/Hseo99cyicr0sktKKqfBkuLrAwnSivXHdgCr/aGj0ZbZfdE5JRM03y9Me/fpYW2gdZDYOW7UOrEm9hEROpIgSYRERGROvDxcOPvl3Vh5m19OV5cyjVTFvP0txs4VuTEE0ObHXrfCnevhN63WXXeX+kFy9/QCauIiLis6EBP7h7Wljn3D+G7Pw9m/JAEdhzI56FP19L7X3MZ994KZq3ZfXYZxCmTwCytvs7uDhHdYVsKTBsK718B2+eDaZ7V8YiI1EnvWyE3Hbb84OyeiIicMQWaRERERM7CgDahfH/fOVzXO5apv2zjklcWsCY9x7md8gmGi5+F8QsgvAt88wAtv7gadix0br9EREROo0Mrfx66oAO/PHQuX/7fQG7qF8fq9Bzu/iCVpH/N4Z4PUpn7216OF5eefmdVZSyDkuPV15UUWcGn+9bB8L9B1jp49xJ4cwRsmg2lZ9iGiFRjGIa/YRgPGobxkWEYtxqG4e/sPrm09heDXytY/qazeyIicsbcnN0BERERkcbOz9ONp6/sykVdWjHhs7Vc+doixg9J4J5hbfF0c+J8xuGd4eZZ8Nv/sM1+BN65GDpfac1XERDtvH6JiIichmEY9IgJpEdMII+N7Miy7Qf5as1uZv+6h6/W7Mbfy42LukQwqnsk/RNDsNuMU+9w/IKKp5mZmURFRVXfPug+6DseUqfDopfhg+shrBMMuh86XwF2XT4ROZFhGA8CdwAJwErgGtM0d5Zt6wnMBQIBA7gamGgYxjDTNNc4qcuuze4OSTdbGZiHdkBQvLN7JCJSa8poEhEREakn57RryXd/Pocre0bx6k9pXDZ5Ib9m5jq3U4YBnS9n3zVfw9BHYdO38EqydQJbVODcvomIiNSC3WbQPzGEp6/syvLHhvP22N4M7xjO12t3c9ObS+n773n87av1rNx5EPNsyt65e0Of2+HuVXDFVCvb6fPbYHKSlWFQdKz+DkqkkTMM4zVgIpAI5ALJwErDMOIMwwgA5mEFmB4BRgD/AYLL1svJ9LoZDBuseNvZPREROSMKNImIiIjUowBvd569pjtv3pzMwfzjXP7qQl6cu5miEueW3zHdvGHoI3DXcmh3Afz0FLzaBzbM0lwUIiLSaLjbbZzbIYznr+vBysdH8NqNvegdH8TMZbu46rXFDJr4E0/P3sD63bl1DzrZ3aH79fCnxXD9TPAJgW/uh5e6wcKXoDCvfg9KpJEpy1a6A1gFBJmmGYwVaLJhBZ+uwcpk6mWa5rOmac4zTXMCMB4INgzj307quusLiIL2F0Hq+1Bc6OzeiIjUmgJNIiIiIg1gWMdwfrjvHEZ1j+TFuVu4/NWFbMw67OxuQWAsXPuuVVLPww8+ugneuwz2bXB2z0RERM6Il7udi7pG8NpNSaz863Cev7Y77cL9eHP+dka+vIBhz6fw4tzNpO0/wpSUNBalZVd7/6K0bKakpJ28AZsNOoyE2+bBmK+gZQeY8wS80Bl+fAryDzTwEYq4rEcBExhmmmYugGmaq4Bry5YJwETTNHdUfZNpmtOAbVgZTnIyybfA0QPw21fO7omISK0p0CQiIiLSQAJ9PHjhuh5MuSmJvYePcfFL85nw6VqKq2Q3nfYiV0NpfQ7cMR8u/g/sWQOvDYTZE6DgkOP7IiIicpZaeLlzZa9o3v5jH5Y9Npx/X9GVsBaevDRvC8OeS+HDZbu49Z0VfLVmN2CNv3fNTKVbdMDpd24YkDAEbv4Kbv8R4gfDL5PgxS4w+xHIzWjgoxNxOb2AT03TrHYXlWmac7ECSQnARyd572dl2+VkEs6FoNaw4k1n90REpNYUaBIRERFpYBd2acUP9w2hd+tgPlqRzgUv/ML2g8fO7CJXQ7C7WXNR3JMKSWNh2TR4JcmqCV9a4pw+iYiInKVgXw9u6BvLh+P6s+TRYTx+SScCfTwoKCrhng9SuWnGRu6cvorJN/RkQGLome08KgmunwF3LoVOl1lj50s94H//B9lbG+aARFxPArD8JNtWAZimufok27dildWTk7HZrKymXYth73pn90ZEpFYUaBIRERFxgGBfDz4a1597hrVhW3Y+Y2Zu5NZ3VvDy9XW4yFXffILhkufhjl+sskBf/xmmDYVdS5zbLxERkbMU7u/FrYNa8+X/DeSXh84lKS6I7QePkVdYxLLtByk4XscbK8I6wBVTKm/WWPcpTE6Gj2+2MoVFmr6ck6zf5tBeNFU9bwK7J6x4y9k9ERGpFQWaRERERBzo/hHtuWVQa0pNKCgq4T8/bGLrPheZVLxVVxj7DVz9llUX/q0L4LPb4PBuZ/dMRETkrGXkHGV7dj5XdwvFbth4ce4WznvuZ/63OhPTNOu206A4GPkf+PM6GHQfpP0IU8+B6VfBzkX1ewAi0nz4BEPnK2DNR1B4xNm9ERE5LQWaRERERBxoUVo2X6RmMrZ3OL6ebmzZl8fFLy9gSkoaJaV1vMhVnwwDulwFdy2Hcx62JiF+JRl++Q8UHXN270REROqkvFzt5Bt6ct+QaN65pTctvNzwdLdx74erueq1RaxOP1mCRi34hcHwJ+G+X2HYE7B7Nbx9EaFf3QSbv4e6BrJEXJdpGIb/iQtlZfEMw2hxku1SW71vheN5sO5jZ/dEROS0FGgSERERcZCqF7lu7xfB62OScLfb6BYdwDOzN3LVa4vYus9F7lj08IXzHoO7lkGb8+DHf8J/+8LGb3WxTEREGp21GbnV5mQakBjK1NFJXJccw6Sru5F+qIDLX13I/R+tJiv3LG6s8AqAwQ9YGU4XPYs9fw/MvBamDLbK62kORGk6pgGHalhuL9uec5LtUxze08YqujeEd4Xlb+n7t4i4PAWaRERERBykpotc/72xF8M6hPHS9T3YcSCfi1+ez1RXyW4CCIqH66bD6C/BzQs+/ANMvxL2b3J2z0RERGpt/JDE382JOCAxlD8NbcO1yTH89OBQ/jQ0ka/X7uHc//zMK/O2cKzoLIJCHj7Qdxx7r/sOLn8NSgrhs1vhlSRY+Q4UF57dAYk4V249LHI6hgG9b4G96yBjubN7IyJySgo0iYiIiDjIqS5yXdYjih/uO4eh7Vry9OyNXD3FhbKbABLPhfEL4MKJkLESXhsA3/0Fjuk6gYiINH5+nm5MuLADc+8fwtD2LXluzmaGPZfCrDW76z5/E4DNHXrcAHcutW7c8A6EWffCS91h0Suae0UaJdM0g0zTDD6bxdnH0Gh0vRY8WsDyN53dExGRU1KgSURERMRFhLXwYuroJF66vgfbs10wu8nuDv3Gwz2roOdNsOS/1p3Zq96D0lJn905EROSsxYb48NpNSXxwez/8vd25+4NUrp26mHUZZ3ljhc0GHUfB7T9ZWcKhbeGHv8KLXeCnp+Howfo5ABFpWjz9oPt1sP4LfU6IiEtToElERETEhRiGUZHdNMRVs5t8Q2HUSzDuZwhOgK/uhjfOg/RlkJdF6KwxkLfX2b0UERGps/6JIXx99yCeubIr27PzufTVBTz4yRr2HT6L+ZvAKoWVeC7cPAtumwexAyDlGXihC3z/GBzeXT8HICJNR/KtVvnN1OnO7omIyEm5ObsDIiIiIvJ7YS28mDY6ia/W7OaJ/63n4pfn8+D57bh1UAJ2m+Hs7lkie8At31uTm895HN4cAcFt8DiYBikT4ZLnnd1DERGROrPbDK7vE8vF3f6fvfuOrqpK+zj+fZLQe2gqPQHbKCUJoKggktjGMqdRh14AACAASURBVAOEpoKIFB3HrojjjE55dQBHxXEEQrOBdLGjgIoCIi2oiAgEEMEBpIoo0vb7x7nRkAmknXtv7s3vs9ZdSc49Z+/nrkXYOWfv/Tyn8p/31jN+4Ube+vy//KFjU/pd2ITyZWKL10H9FOg5CbavhoVPweKRsCQDWvSEC+6Amon+fBARn5lZNSADcM65HjmOP1bAJpxz7sGgBBeN6p4NDc+HZePh/Nu8HZIiIiWMJppERERESqjs3U3nJ9bkT6+s4tG31jB71TaGp7cgsXblcIfnMYPm6XDGFTDvr7AkAwPIfBE6DIYqdcMdoYiISLFULV+GIVeeRc82DXn0rS8Z/s5XvLxkMw9eeRZXnHMKZsVcAFL3bOicAR0fhIVPe7sWMl+Es38HF90Np5zrzwcR8Vc64IAeOY4NLuC1DtBEU2Gk9IOZN8OG96Fpp3BHIyLyPzQFLiIiIlLCZe9ueqp7S7K+O8CVIz5izIcbSk7tJvDyxx876hU9Bzh6CKb2huIUUBcRESlBGteqREbvFCbd3JbK5eK4deIKumcsZtXWYtZvylajsbcb+M7Pod3tsG4OjLoQJqbD1x/704eID5xz+/Ammrrleiu5gK+UkAUbLc6+BirW8nY1iYiUQJpoEhEREYkAZsbvWtVjzt3taX96bf7vrS/pNvpjsr4rIbWb9m+DlRPh2OFfj32zGGb0gyM/hy8uERERn7VrWos3b7+I//v9Oazf8QNXP7OAwdM/47v9Po13VepC2l/hrlVwyUOwdTlMuBzGX+FNPmkRh5QAzrkZzrkZuY5lFvQVrrgjVlw5aHU9fPUW7Nsa7mhERP6HJppEREREIkjO3U3rd/xQcnY3zR8G7tjxxywWVs2A567yJqJERESiRGyMcV3bRrx/78X0u6AJM1ZsoePjHzDygyx+PnLUn04qVIf298Gdq+DyobB3M0zsCqMvglUzvZ3EIlJ6pPT1JppXPB/uSERE/ocmmkREREQizC+7m+5qz0XNft3dtCGcu5u2LPHS5eXkjkL1hrB9FWR09FZki4iIRJFqFcrw0FVn8+5d7TkvIZ6hs9eQ9sSHzF61DefXzqOyFeG8QXB7Jlz7Hzh8EKb3hWdaw4oX4Mih/NsQ8ZmZNc7n/UvM7N48XjeHJsIoVKMxNE2F5c/D0cP5ni4iEkpx4Q5ARERERIqmTtXyjOmdzKyVW3nktdVcMeIj7rvsDPpe0ITYmGIWJi+sQQt++Xbr1q3Uq1fv1/e2fQ4v9/JS/lzzb2jRPbSxiYiIBFlC7cqM7dOaj9Z9x9/fWM2gl5ZzfkJNBrapRc4hsVjiynqps1r0hDVvwEf/gtf+CO8/Bu3+CMl9fOpI5OTMrAmw3sxWOOdan+C0S4H7gNx/lDozm+uc2xTMGKNW637wcg8vhd7Z14Y7GhGRX2hHk4iIiEgEMzN+36p+YHdTLf7x5pd0D/fuptxOORcGvA8N2sArA+Ddh5TuR0REotJFzWrz1u0X8fdrf8Oabd9z05SvGDLzc3b+4GO9wphY7wHzgPlw/UyomQjvDIEnz6HKipHw0x7/+hLJ2+DA1/4FODc9x6sb3sTTgCDFFf2aXQrVGsDSceGORETkOJpoEhEREYkC3u6mFJ7o1oK12/dzxYiPGPtRCajdlK1SLbjhFWjdHxb9Gyam60GYiIhEpbjYGG44vzEf3NuRLs1rMW3ZN3Qc/gEZH2Zx6Mix/BsoKDNo2glufAP6zYEGbam6/N/w5Dneog7VR5TgSQH2OudW5neic25Gjtd0YC+QFvQIo1VMrLd7ceN82Lk+3NGIiPxCE00iIiIiUcLM6JxUn7l3dzhud9PGnQfCHZontgz89nG4egRs/BDGdILv1oY7KhERkaCoVrEMd7avz+w725PSuAaPvrWGS5+cz5zV2/2r35StQRvoNZntXWbBGVfAx/+Bp86F1++E3Rv97UsEEoBl+ZxzojzOywLXS1G16g0xcbBsfLgjERH5hSaaREQkqphZJzN7zMyq5jjW2MzeMbOjgdej4YxRJNhy7266/KkPmZy5o+Tsbkq+Efq8Dj9/D2M7wdp3wh2RiIhI0DStU5kJfdvwXN/WxMXG0P+FZdwwbglrtn3ve19H4k+HLmPhj8uh5XWwciL8Owlm3Azbv/C9Pym1quPtTDqZUXh1mnLbG7heiqpKXTjrGu/3+/BP4Y5GRATQRJOIiESfgcAA51zOO/e5QCowD1gJDDaze8IRnEioZO9umnN3By5sWot/L/iWHhklaHdTo/Oh//sQ3wQmdYePngC/V3eLiIiUIBefUYe377iIR64+m8+37uPKER/x0KzP2eVn/aZs8Qlw9VNwx2dw/h/gq7dhZDtvzP1mif/9SWmzAUg62QnOuY3OuXl5vJUUuL7UGDU/i0VZO487tihrJ6PmZxW90db94OBeWDWzmNGJiPgjLtwBFISZDQASgazA16WBvK5FbSd75USWc26Yb4GKiEhJkArMyf7BzLrgpWaY5pzrHji2HhgE/MuPDjVOSUlWt2p5xvZJYdy8VTy94FuuGPEh9112Jn3bNSYm5kQZTUKkegPoOxteuw3m/RW2r4JrnoGyFcMbl0gU0RglUrKUiY3hxguacG3LeoyYt44XF3/Nqyu/5Y5Ozeh9fmPKxvm8HrjqqXDpP+DCu2HpWFg8EsalQaML4aK7ILGTV+tJpHBmAPeaWUfn3PsFvSjHvdlQP4Mxs/vxxiiAeGCDc26wn30UR/P61bhtUiaPdT6XWrGH+DprJ7dNyuSZXq2K3mijC6D2mbBsHLS6zr9gRUSKqMRPNAUGi5o5BwgzG21m8c65jEK0MxSYkvMaM+tqZtOcc+n+Ri0iImFUneNXyKUBDpiS49gKoIsfnWmckkhgZlxxVjxXt2nGkJmf8/c3VjN71X8Z3rUFjWtVCm9wZStCl3FQ9xyY9zfYuQ56TPImoUSkWDRGiZRcNSqV5ZFrfsN1bRvy9ze/5B9vfsmkTzbzp9+exSVn1sH8nvypGA8d7vd2Ny1/Hhb9G17qAqe28CahzroaYmL97VOi2SjgPmCamXVyzn2a3wVm1hIYg3dvNtqvQMxsNDA65+IHM5tjZsudc8l+9VMc7RJrMaJHS/qMX0L9auX44bDjmV6taJdYq+iNmkHKTfD2/fBtJpxWjEkrEREflOjUeWZWHRiSxyqEwcDQwPsFaScVb8XdipzHAyv5dgfeFxGR6JA753f2//FzcxwrSE7xfGmckkhTt2p5xvVJ4V/pLfhq234uH/Eh4xds5Fi4azeZwUV3Q68psGcTjOkIX38c3phEIpzGKJHI0KxuFZ7v25oJN7YGg37PL6P3+CWs274/OB2WrQTn3wp3rIRr/g0//wDT+sB/2kLmS3DkUHD6lajinNuIlyEiHlhhZs/mrJGbk5lVNbORwHK8+7BBzrlNfsQRGIPm5B6j8HZMJZlZVz/68cNFzWrTunE8m/f+TNrZdYs3yZStRQ8oUxGWjit+WyIixVSiJ5qAAcCy3Aedc3vxVqt3K2A7aZw4/+sc8skrKyIiEWUaMMDMHjWzKXipGabnqtmUQh7jSxFonJKIY2Z0Sa7Pu3d1oF1iLf72xmp6ZCxmU0mo3XT6ZXDzPChfDZ6/GpZNCHdEIpFMY5RIhDAzOp5Zh3fubM+frzqbT7/Zy+UjPuLhV1ex50CQJn7iykFSb7htKXSdAGXKw6t/gKdbweJRcOjH4PQrUSOwy3UQYHh1cveY2VIzm2JmjwW+LgX2BN43IN05N8bHMNKAMXksnsgetxJ87KtYFmXtZO32/ZSNNWau2PI/NZuKpHw1OLcrfD4dfir2OkoRkWIp6RNNJ7up2RB4v6AGnuB465P0ISIiked+YCXwAJCO9398/+w3zaw/3ko6P/KCa5ySiHVKNW930+PpLfhy2/clZ3dT7dO9yaaEDvDGnfDmPXD0cHhjEolMGqNEIkyZ2Bj6XdiED+7rSK82DXlx8ddc/PgHTFi4kcNHjwWn05hYOKczDPwIrpsB1RvC7MHw1Dkwfzj8tCc4/UpUCEw2JQIz8SaSkvHuwQYHviYHjmcAic65GT6HsBTYncfx7Amm3DudwmJRoCbTf65Lom+bUzh81DHoxeX+TDal9IMjP8Gnk4vflohIMZT0iaYUvKK1edlNwVfPTQG6BvK25pZUlGK4IiJSMjnn9gVycScCyc65prl2M00F0pxz7/nQncYpiWhmRtfk+sy5qwPnJ9QsObubKlSHXlOh3e1e4fIXfgcHfLgRFyldNEaJRKj4SmX5++/O4e072nNuvWr89fXVXP7Uh7z/1Y7gdWoGzVLhprfhpnegXgq8/w948lyY8xfYvz14fUtEc85tdM6lO+di8BYxDAaGBb6mOedinHODAun2/O57unMuMbBbN6fBwArn3Ny8rgu1z7bs+6UmU9fmtahZqSyNalbksy37it/4aS2hXjIsGw8uzAvGRKRUK+kTTSfLG74XLxdsvgK5WofhpVLKMrMEM6seuFk60eo8ERGJYIEbnsw8ju9zzs3zqRuNUxIVTqlWnvE3tmZ41+a/7G6asDDMu5tiYuHSv0PnMbB1GWR0hG2fhy8ekcijMUokwp1xShVe7NeGsb1TOOag74Sl3DhhCet3/BDcjhueB9dNhUEL4PRLYdG/4alz4Y27vVqKAPu3Uev13pqAkuM45+Y554Y75x4IfPXrvqvAAnWZ4oFOoe77RAZ1SPylJlPFsrEM6pDI51u/J6lhDX86SOkHO7+CTQv8aU9EpAhK+kRTfgpUwBYgUAR3IN722SxgmnNuoHNOqR5ERKKImXUK5ASvmuNYYzN7x8yOBl6PhigcjVMSMcyM9JQGv+xu+uvrq+kxZjFf7wrz7qbm3aDv23DsCIy7FL6YFd54RKKHxiiRCGBmpJ5dl3fubM+frjyL5Zv2cPlTH/LIa1+w98cg1W/Kdsq50HU83LYMWvSAzBfh6SSYOQBmD6HstuUw349s1CLFE1gEcb+ZzQG6A53y2OVUYlx/XiNqVynHv979CufHLqRzOkP56rBsXPHbEhEpIvPlP7QgCBTy2wMMds4Ny+P9ocD9zjkrRJsD8FIpdeXX4vDp+Zw/AKBevXrJn3zySeE+RBEdOHCASpUqhaSvUPenzxaZ/UVrX6HuL5o/W/369Zc751JC0lk+zGwq3o1FzRzH1gNNgHlATaAl3hjyr2L0E9ZxKlxjFOj3JhL7Kmx/zjneWrObpz/cypFjMKjdqXRpXosYK9g/52B8tpgfvyN+zh2U27GS71vdwv7kP4DFBK2/E4nWvkLdX6g/W0kap0Ih3GNUjvN1LxWhfYW6P322gtvz42HGfLKN17/YReVysdzc9hSuPacWcTEWlP5yijmwncqfP0el1VOIOXoQgGOx5dje412OVawdlD6zRfO/kUgao8yssXNuU0lu38wSgGnAYydK71oS7qWmffodT324lRG/SySlQZVit1vt46FU+mIi23rN++X3MZp/b/TZIrM/fbbI6wsKMU4550rsC3B4N0B5vTfUC7/AbY0GUnP97IDlQPX8rk9OTnahsmXLlpD1Fer+9Nkis79o7SvU/UXzZwOWuRIwbnihsBuYkuPnLsCxXMfWA+t86KtEjFOhHKOc0+9NJPZV1P6+3fuj6zP+E9do8BsufdQit2nnD0Hrq0AOH3Ru1q3OPVzVuUk9nPtpX3D7y0O09hXq/kL92UrSOBWqV0kZo1yIxyn93kRmf/pshbf6232ux+iPXaPBb7jUf33g5n+1I6j9HeeVW517pLo3Hj9Sw7nX7wp6l9H8bySSxqjAfdSjQWq7P3DUp7aSAuNUan7nhute6qdDR9x5j851v//PAnfs2LHiN/zdOu93cv6w/+krVKLh/9aS0J8+W2T2F619OVfwcSrSU+cViJndDyx3OYoAOucGAul4g8+YcMUmIiK+qw7kTOWThneTMSXHsRV4q7FLBI1TUlKdWq0CE25szbCuzfnyv99z+VMf8Vw4azfFlYNrnoErhsHad2BcGuxW5i6RYNIYJVIynXVqVSb1b8voG5I5dPQYvccvod9zS9m852BwO96/DVZNB3fM+9kd9VLqqVZTaTEIeMDMlpjZ7/1o0MwuMbN3gFGB9ovNefUFN+AtrCiRypeJ5bZLmrJi814+WPtd8Rus1RSadIDlz8Oxo8VvT0SkkEr6RNNevBRHecn9IPFkBjrnMnIfdN4W2jS89A8iIhId9nJ83YnUwNe5OY5VD5znR18apySqmRndUhrw7l3taZsQzyOvr6bnmMVs3vVjuAKCtgPhhpnww3bI6Ei5rYvCE4tIyaYxSiTKmRmX/eYU3r2rPQ9ccSafbNzN9ZPW8Pc3VrPvp8PB6XT+sF8nmbIdPQSzhwSnPylRAosOmgKxwAwz22VmjwYmi6rmc/kvAuffa2brgDl4qVlTnHN+Ll7YgLcgosRKT25A/RoVeHLO2uydWMXTuh/s+wbWvVv8tkRECqmkTzTN5cQrzhM4/qFhngK5WU94ExUYJDcE8piLiEjkmwYMCNzwTOHXOhLf5zgnBVjmQ18ap6TUyLm7afW333PZUx/y/KJN4dvdlHAx9H8fqp5GzbcHwMfPgh836CLRQ2OUSClRLi6WQR0Sef/ei7nyzHjGL9xIx8c/4KXFX3Pk6LH8GyiMLUu8iaXc1rwOP+72ty8pkZxzG5xzyUA3YBPwAN5k0Z7AxNM7gdcUMxsZ+DolcGydmR0NnD8MMGCQc66pcy6zMHGYWXUzc2Y2Or/zivI5Q6FsXAy3d2rGZ1v2MWe1D7sCz7gSKp8CS8cVvy0RkUIq6RNNSzn5zdHyArSx+yRtZNvrnPNjZbuIiITf/cBKvBuedLwHZP2z3zSz/ngruf1Io6BxSkqVX3Y33d2eNk3iefi1L8K7uym+CfSbw8FGl8A7Q2DWrXA4yCmDRCKHxiiRUqZ2lXI80Kkhr992IU3rVOahWav47dMLWLh+p3+dDFoAj+yDR/axtf9q7/t+gXnrqb3haJB2UkmJ45ybHphwqgHcAryHN3GUFnilA9mpVtMDx2oCmXj3aomBCabi7mI60RiUQASMUZ1b1aNxzYo8MWdt8RdwxZaB5D6wfi7s2eRLfCIiBVXSJ5oygKTcqw8CK+vigam5jlc3s9ScxwIDyl4zy3O7bKAtP1a1i4hICeCc2xe44UkEkgM3Lzl3M00F0pxz7/nQncYpKZVOrVaB5/q2ZlgXb3fT5SM+pP8Ly1i47vgHWYuydjJqflZwgylXmd2pT0GHB+DTSfDcb736ESKiMUqklDqnXjWmDDiPkdclceDQEa4b+wk3P7+MTTsPBKfDBq3h6qdh00cw+4Hg9CElVuD+K8M5l+aci8ebeEoEknO8EoEazrl451yKc264c25jMfvdC2Q45wbnfi8wPiUAjxWnj1CIi43hjtRmrNm2n7dX+fA3bFIfsBhYNqH4bYmIFEKJnmgKDBqD+d9V50OBwXmsSpgHzMl9g4S3cmJM7hukwMAzNFDMVkREokjgxmVPHvnCHeDLk2+NU1KamRndWjfgnbvak9I4njmrt9NnwhJmZW4FvEmm2yZl0rx+tRAEEwMdh0C3F2DHl5BxMWwpyGYNkeilMUqkdDMzrjj3VObe3YH7LjuDj7N2kvbkfB5960u+PxiEXUcte0K722HpWKXtKuUCE08bnXOZOV4bnXP7gtDdUDMbnUd6vNHAXOfcsCD06btrWtSjaZ3KPDl3LUeLu6upWj044wpY8Ty1Xrse9vuQkk9EpADiwh1Afpxzw8xsgJkNxXswmAhMCRSfzW0ueRS2dc5tMLNOwBAzG4KXAgIgyzmXHsTwRUQkDMysMzCEX4u/puGlcgB4ELjPzBKcc18Xty+NU1LanVa9As/3bc3UZd/wyGtfcOeUlZzfqApf7fyZZ3q1ol1irdAFc/a1EJ8Ik3vChCvg6hHegy+RUkpjlIiULxPLHzo2JT25PsPf+YoxH21gxvIt3HPpGXRv3YDYGPOvs9RH4Luv4O37oVYzaNLev7ZF8hAYowbjjVHgjWPxwJxImWQCiI0x7kxtxm2TMnn902/5Xat6xWsw5SZY8wZlf9oL84fCVU/4E6iIyEkUeqLJzJYCk4ExuVIRBY1zLqOA5w3GW7WX13t7T/SeiIhEj8DDsOl4D8oeINdKbufcA2Y2IHC8hx99apyS0s7M6N66IRc1q033jI/5+Ov9JDWsznlNaoY+mFPOgf4fwLQ+MGsQbF8FqX+F2BK/vkokKDRGiQhAnarlGZ7egt7nN+Zvb3zBg698zouLv+YvV53N+Yk+jdcxsdBlLIxN9eo19X8P4vMr8yZSPNEyRl15zqmcecp6Rsxbx1XNTyUuthhJqGqfBRiGg5UTocNgqFLXt1hFRPJSlP+1koFheOmIlphZv1wpiURERMJpMN4q66Z49SnyMhdvPBMRH23adYADB49yZp0KrNi8lz7jl3D46LHQB1KpJtzwCrQZAB8/A5PS4ac9oY9DRESkhDm3fjWmDjyfZ3q14vufDtNzzGIGvriMzbt+9KeD8lWh58vgHLzcEw6GZH2ySMSLiTHuSjudjTsPMDOQirrIPnrcSy0NcOywt6tJRCTIijLRVAO4BS8FUQreQ7w9ZjbbzH7vZ3AiIiJFkIo3kXQyu/GKw4qIT7JrMj1zXSvGdjudbin1+Wj9Tjo/u5Affj4S+oBiy8CVw73i5Bs/gjGXwI41oY9DRESkhDEzrmp+GvPu6cC9l57OR+t2kvrEfP759hr2+1G/qWaiVzdx5zqY2R+OHS1+myKlwKVn1+XcetV4et46Dh0p4mKt/du8XUwu8Ht37ChkvqhaTSISdIWeaAoU9ctwzqVx/KTTpcAMMztqZpPNrKPPsYqIiBTECryFECeTGjhPRHzy2ZZ9v9RkMjOGdW3BgIsSWPXt9/TMWMx3+38OT2DJfeDGN+HnH7xUPl+9HZ44RERESpjyZWK57ZJmvH/vxVzV4lRGzc+i4+PzmbJ0M0ePueI1ntABrhgKa2fDvL/5E7BIlDMz7k47nS17fmL68i1Fa2T+MHC5JqmOHoI5fy5+gCIiJ1GMhJ/HTzo552Lw0hCNAdKBuWa2y8yeNbNGfgQrIiJSAFOBJDPrl9ebZjYKaAKMDmlUIlFuUIdE2iXWOu7Yg789i3F9Uli3Yz9dRy3i610HwhNcw7Yw4H1vhfXLPeHDx72UPiJhZmaNzeySnKnIzayqmTUOX1QiUtrUrVqeJ7q15NU/XECjmhUZPONzrnlmAZ9s2FW8htv0h5SbYOFT8Olkf4IViXIXn1GbVg2r88x76/j5SBF2A25Z4k0s5bb6VW/hlYhIkBRroilb4OZoJN7DvQGA4U04vQcMAjYEdjmplpOIiASVc24Y3viTASwDHJBuZiPNbBfeODXdOTc2jGGKlBqXnFmXSf3P4/ufDtNl5CI+37IvPIFUqw83zYZzu8J7f4fpfeFQmCa+pNQzs85mthTIAuZw/E7cB4EsLdYTkVBr0aA60wedz4geLdlz4BDdMxZz68TlfLO7GPWbrhgGjS+C126HLcv8C1YkSpkZ96Sdwbf7DjJ5yTeFb2DQAnhkHzyyj639V3vfXz/Dm3x6ZSAcC0P9VBEpFYo80WRmLc3sscBDuznAQGAfMNA5F+OcG+ScS8dLrzcE6Eb+NTNERESKLZDedQhQE2/xw8DAy/DGqe5hDE+k1ElqWIPpt7SjfJlYumd8zIdrvwtPIGUqQOcxkPY3+GIWjL8M9m4OTyxSaplZJ2A63n3SA3hj0y+ccw/g3VepcreIhJyZcW3Lesy752LuSj2d99bsoNMT8xk2e03Rai7GlvHqNVU9FSb3gn1b/Q9aJMpc0LQmbZrE85/313PwsA81zpqmwuX/hDVveAuuRESCoNATTWZ2r5mtA5YDg/FujIYDic65FOfcmJznB9LrDcNbWZ7sQ8wiIiL5cs4Nc87F4z3ISwZqOOfic49TIhIaibUrM/OWdjSqWYmbnlvKK5lFzDtfXGZwwR1w3TTYsxkyOsKmheGJRUqrwUCWc64p3j1SXuaieycRCaMKZWO5I9Wr33TlOafw7AdZdHz8A26duJyF63Yed+6irJ2Mmp914sYqxkPPyXDoR2+y6VAxdkhJxFB62KLzdjWdzo79P/PS4q/9abTNAEjuCwueUCpLEQmKouxoGgYkAvOA9MBDuweccxvzuS4Bb2WeiIhIyAQWPGQ65zQGiYRZnarlmTLwPNo0ieeuKZ8yen4WLly1kpqlQf95UKE6vHANLB0XnjikNEol/0wPu/Hun0REwurUahV4qkcrZt7ajnrVK/DW59voPWEJExZ6j4AWZe3ktkmZNK9f7eQN1TkLuoyF/34Kr/5BtRKjmNLD+qNtQk0ubFqLkR9kcaAouwlzM4Mrh0OT9vDaH2HzJ8VvU0Qkh6JMNA3GWxV+qXNuRiGuG4hXfF1ERERESqmq5cswoW9rrmp+Ko+9vYa/v/Elx46F6WFTrWZw8zxI6Ahv3g1v3AVH8iieLOKvFRz/0C0vqYHzRERKhKSGNZh5Szue6t6SquXj+OvrqxkwdS23TcrkmV6taJdYK/9GzrgcUh+GL2bCh48HP2gJOaWH9dfdl57OrgOHeP7jTf40GFsG0p/3apdO7qUU0iLiq0JPNDnnhuMNGHnK3hqbx3UbtZpcRERCIbCKboqZLT3Ja0m44xQprcrFxfJ0j1b0vaAx4xdu5PbJmfx8xIf880VRoTr0mgIX3AnLxsML18IPYaohJaXFVCDJzPrl9aaZjcJboDc6pFGJiOQjJsb4Xat6LHzgEs6pV5Uvtv9IcqMaBZtkynbBndC8O7z/D/jy9eAFK+Gi9LA+SmpYg45n1Cbjww3sP3jYn0YrxkOvqXD0MEzqAT/v96ddESn1ilKjqQveNtfOJzglDZhjZi2KFZmIiEgRmNl9wDQgHe8G5mQv1OGT/QAAIABJREFUEQmTmBjjL1edzZArzuSNz/5L3wlL/buBLnQwsZD2V+g8Fr5dAWM6wn8/C08sEvUC9Wvfw3sAtwxwQLqZjTSzXcAAYLpzbmwYwxQROaGV3+xl656fqFu5DHNWb2f6sm8KfrEZXP001EuGmQNh26rgBSrhoPSwPrs77Qz2/niY8Qs2+ddorWbQ7Tn4bg3M6A/HwrTgS0SiSlFS5w0BNjjnZub1ZqDI+r7AeSIiIqE2MPA1HS/Va8wJXrHhDFJEvELHAzsk8mT3FizZuJtuoxez4/uD4QuoeTrcNBvcMRh3KazK889dkWJzzqXh3S/VxEsrNDDwMmCgc657GMMTETmh7JpM/7kuidHpp1O1fByDZ3zOB2t2FLyRMuWhxyQoXw1e7qmdxNFF6WF9dm79alx6dl3GLtjAvh99XJSVeAlcMRTWvg3z/upfuyJSahVloimJ/AeEZWiluIiIhEcC3krwGUrZKhIZft+qPuNvbM3Xuw7QeeQisr77IXzBnNYK+r8PpzaH6X1h3t/h2LHwxSNRyzk3zDkXj5eWPBlvcUR8YOGeiEiJ9NmWfb/UZKpduQzP9EriqHM8MWdt4Rqqcgr0mAgHdsDUG1QjMXooPWwQ3JV2OvsPHmHMRxv8bbhNf2h9MywcAZkT/W1bREqdokw0FcRetA1WRETCIxMvHYOIRJD2p9dm8oDz+OnQUbqOXETm5j3hC6ZKXejzOiT1ho8e94olH/w+fPFIVDGzS8ysZfbPzrl9zrlMLY4QkUgwqEPicTWZ2p9em9s6NuWzrfuYuWJL4RqrlwS/exY2fwxv3g3O+RythJrSwwbHWadW5bfnnsqEhRvZfcDnSdnL/wkJF8Prd8DXH/vbtoiUKkWZaMrE2+Z6MgXJySoiIhIMNwPdVCtQJPI0r1+dGbe0o2qFMvQcs5j31mwPXzBx5bwaElc+DuvehbGpsCsrfPFINJnOiQuki4hEnDtTm9G2STx/emUV63fsL9zF53SB9vdB5ovwyajgBCghpfSwwXFnajN+PHyU0fN9/ns0tgykPwc1GsGU62DPJn/bF5FSoygTTY8BNcxssplVzfmGmVU1sylANbxC7CIiIqHWDdgIrDCzJYHVc3m9ng13oCLyvxrXqsT0Qe1oVqcK/V9YztSlhSgw7jczL6VI71lw4DsY05FyWxaGLx6JFtOAZDNrFO5ARET8EBcbw9M9W1GxbCx/mJjJT4eOFq6Bix+EM6+Cdx6E9fOCE6SElNLD+q9Z3Spc2+I0nv94Ezv2+1zTtEIN6DUVjh2FST20k19EiqTQE03OuenAGLwHeXvM7B0zm2Jm7wB78IqvZ2gbrIiIhMlgvHqChleIduBJXiJSAtWuUo6XB5xHu8Sa3D/jM555bx0unOl0mrSHAe9D1frUnD0QFj2j9D5SHPcD+4A5mmwSkWhRt2p5nuzekrU79vPIa18U7uKYGPj9aKhzNkzrCzvXBSdICbrAM8J7s38+WXpYM+tsZo+Z2e9DG2XkuiP1dA4fdYz8IAi77GsmQrcXYNc6mNHPm3QSESmEItVocs4NxJto2gSk4U0upeGtIE93zt3iV4AiIiKFlFzAV0q4AhSR/FUuF8e4Pq35fat6PP7uWv7y6hccPRbGyZ0ajaHfuxxs1Ane/RPMugUO+7yaVEqL/njF0psCG8xsqXbeikg0yK7XNGXZN4Wv11SuMvSYBLFx8HIP+CmMtRqlOFrjpcw7KTNbirfDdzAw3cwmBzuwaNCkViU6t6rHxE828999P/nfQUIHuHK4lzZ6zl/8b19EolpcUS8M7GyaDmBmTZxzG32LSkREpIicc5nhjkFE/FE2LoZ/pbegTtVyjJ6/ge/2/8xTPVpSvkxseAIqV5ndqU9Sb/0k+OBR2LkWur8EVU8LTzwSqYbl+N74dQFEbg64NSQRiYj45I5OzViycTd/emUVzetXo2mdKgW/uEYjb1x9/hqYfhP0muZNPEkkWQbebiW8SSeAJc65V7JPMLMueOPecmAA0AO418ym5DxP8nZ7p2a8krmV/7y/nn/87lz/O0i5CXasgY+fgdpnQFJv//sQkahUpB1NuWmSSURESiIza2xml+SsKRioJ9g4fFGJSGHExBhDrjiLP191NrO/2EbvcUvY9+Ph8AVkMXDxYOg+Eb77CjI6wjdLwxePRCLtvBWRqJWzXtOtE1cUvl5To3Zw1ROQ9R7M+XNwgpRgmoaXIjZ7t9JgYIaZrc2RLrY73mKK/oG0eoOBTGBQOAKONA3iK9KtdQOmLP2GLXt+DE4nlz0KiZfAG3fDpgXB6UNEoo4vE00iIiIlSSDf91IgC5jD8Q/rHgSyVBdDJLL0u7AJT/dsReY3e0gfvSg46UIK46yroN8ciCsHz10JKyeFNx6JGIGHagV6hTtWEZGiyK7XtG7HDzz82qrCN5DUG9reAoufhRUv+B+gBFMy3m7d4YHvE/FKb8Ti3ZcBJAS+bshx3RS0wKLAbuvYFMN45r31wekgNg66ToD4JjDlBti9If9rRKTUK9JEU2CF+DtmtsvMjp7gdcTvYEVERPJjZp3wUrvWAB7Au9H5hXPuAbwi7ENDH52IFMc1LU7j+b5t+HbvQTo/u4h12/eHN6C6Z8OAD6DheV7NptlD4Kj+BBYREcmu1zR12RZmLC9kvSaAS/8BCR29HRVff+x/gBIs3YBpzrkHAosmNgZKb6QDiTkzSzjnvs9x3V6gekgjjWCnVa9Ar7YNmbZ8C1/vOhCcTipUh56TAQeTesDBfcHpR0SiRqEnmsysFd4K8TS8h3cbc3zN/t6Alf6FKSIiUmCDgSznXFMg4wTnzCXvehgiUsK1a1qLKQPP48gxR9dRH7Ns0+7wBlQxHq5/BdoO8lZeT+wCP4Y5JokYgQV8nc3sMTO72cxahjsmERG/3NGpGW2bxPPQrFWs31HIxSGxcZA+wavbNOV6YvdvDU6QEgx5/SHk8rkmkeN3OEk+br04kbgYY8S8dcHrpGYidHsRdmfBtL5aUCUiJ1WUHU1D8VaCJzvn4gMP8gAGBL5vircS4VGfYhQRESmMVLyJpJPZza8pG0QkwvzmtGrMvKUdNSuV5bqxn/Bh1t7wBhQbB1cMhWuega8XwZhLYMeX4Y1JSrRAvcApeAv4sutYZADLzWxyztqCIiKRqtj1mirU8HZUHD1MzXdvg59/CE6g4qdpwAAzuyewmKKqmV0CTAX2Ouc2Edi5ZGZVclzXFVgR8mgjWJ2q5el9fiNmZW5l/Y4g/m40uQh++wRkzYN3HwpePyIS8Yoy0ZQKjM6VM/yXLa7OuQ14A8jA4ocnIiJSaCvIP793KrqREYloDeIrMv2Wdpx1alX+9PYmXlr8dbhDgqQb4MY34dABGJsKa94Md0RScr2Hl0ZoBl7x8zS8+6f38NIOLQtfaCIi/il2vaZazSB9AnF71sErA+HYMf+DFN8457LHsuF4iyn24NVmSgRqBOroJuBlQpoX2M37DtAEeCw8UUeuQR0SKV8mNri7mgCS+8B5t8InI2HZ+OD2JSIRqygTTXktGd0AtM51jor4iYhIOEwFksysX15vmtkovBuZ0SGNSkR8F1+pLJP6t6Vtw6o8NGsVT8xZi3P5ZWYJsgZtvLpNtZrB5F4wfziEOyYpUczsn0ArINU51805N8Y5Ny/wNQ1v4qmpmSlDhIhEhWLXa2raiX1t74c1b8AH+q+xpAuMZZfiTTaNwRvXagSOzcNbaNEN77lhBt5iiweccyrBUUg1K5fjxnaNeeOzb/lqW5Brl6b9HZqmwVv3wcYPg9uXiESkokw0LcNbCZ7TVLxtrtm6oiJ+IiISBs65YXir6DLwxiwHpJvZSDPbBQwApjvnxoYxTBHxScWycfzzt01IT67P0/PWMWTm5xw5GubVztXqQd+3oXl3eP8fMK2Pt8tJxJMKzHXOvZfXm865DLxdt2khjUpEJIjuTD2d8xKKWK8JOHDODdDqevhwOKyaEYQIxU/OubnOuQecc4MCCyn25Tg2wzk3HW/yKR1IdM4ND3PIEWtA+wQql43jyTlrg9tRbBx0HQc1m8KUG2BXVnD7E5GIU5SJpgwgOVeh2mlAopmtM7N1eNtg86uPISIiEhSBVXRDgJp4aRkGBl4GDHTOdQ9jeCLis7hYY1jX5tzWsSmTl37DoJeWF74OhN/KVIDfj/ZWf375Ooy7FPaUgPR+UhIkkX/B8w2B80REokJsjPF0j1ZUKufVa/rx0JHCNWDm1YlpeD7MuhW+zcz/GinRApNPM5xzG8MdSySrXrEsN13YhNlfbGPV1n3B7ax8Na9umsXApO7wU5jrpIpIiVLoiabAqoNkYGOOYxvxtr3Wwsu7Oj3ws4iISFg454Y55+LxVsolAzWcc/HOuTFhDk1EgsDMuPeyM/j7tb9h3podXDd2MXsOHAp3UHDB7dBrGuz9BsZ0hE0LwhuTlARzyT/NeBKqJSgiUaZOznpNr35R+AbiykG3F6FSbXi5F+zf5n+QIhGo30VNqFahTPB3NQHEN4HuL8GeTTDtRjhayEljEYlaRdnRhHMu0zm3L9ex6c65Gs65mECu8SBPo4uIiPwvM6ua8+fASrnjxi0z65z7PBGJDjec35hneyWx6tvv6TpqEVv2/BjukKBZKvR/DyrEwwvXwtKxqttUuk3HyxBxT15vqpagiESzi5rV5o8dmzJt+RamF6VeU+Xa0PNlOLjPq4V4+KD/QUqxmFljM3vHzHaZ2dETvDQ74aOq5cswoH0C89bsIHPznuB32PgCuOpJ2PA+vDMk+P2JSEQo9ESTmV2SK22eiIhISbLnRA/vAMysGjAW6B+6kEQklK4491Re6teW7/b/TOdnF/Hlf78Pd0hQqyn0nweJneDNe+CNO+FImHdcSVgEajDNAIab2dpADcF7c9USnKtagiISre4I1Gv686xVrNte+HpNnHIudB4NW5fD67dr8UYJYmatgCy8OoOGlw0p+2v29wasDFeM0apPu8bEVyrLE6HY1QSQdAOcfxssyYAlY2D/Nmq93hv2bw9N/yJS4hRlR9N0vDpNIiIiJVH2zUueAjub5gI9QhaRiIRcmybxTBvUjhgzuo36mI+zdoU7pEBe+5fhwrth+XPwwjXww3fhjkrCwDmXDgwCmuLVEBwW+FoDGOycuyyM4YmIBFWx6zUBnHU1dHwIPpsCC0f4H6QU1VBgH5AcSFveNHB8QOD7psBe4NFwBRitKpeLY2D7BD5at5Olm3aHptO0v0Gzy+DtwfD6HZTdthzmDw1N3yJS4hRlomkaXqqHRn4HIyIi4pMTLms0s8Z4tS9UZF0kyp1xShVm3tqOutXK02f8Et787L/hDgliYiH1YegyDr5dCRkXe1+l1HHOZTjnYvBq3KbjPZSLcc4ND3NoIiJBl12vaf13RazXBND+XvhNZ5j7CHw129f4pMhSgdHOucwcx/YC1QGccxuAqXiLK8Rnvc9vTK3K5fjXu1+FpsOYWOgyFuITYO1sDAcrJ2pXk0gpVZSJpvvxVifM0WSTiIiUBGZ2LDvfd+DQsBPlA8dL5ZCAiqyLlAqnVa/A9EHn07x+NW57eQXPLdwY7pA853aFmwIPxcZfDp9PD288ElKBRQ8AOOc2OudmZD+UC9S2uCRcsYmIhEqx6zWZwbX/gVNbwIx+sONL/4OUwtqbx7ENQOtc56SEJpzSpULZWG69OJHFG3azaP3O0HRaviqc1urXn48d0a4mkVIqrgjX9MdbfTAA2GBmK4BleZznnHO3Fie4bGY2AG+lX1bg61LnXIHvxs0sFW+V4DRgN3kPfLudc3kdFxGRkm8ev+5iSsXL/32i/9N3400yPeZX5xqnREq26hXL8tLNbfnjy5k88vpqduz/mfsuOwOzE2bZDI3TWsKA92Fqb+8B2fZVcMmfvdWhErXMrAsw1czSnXMz8zglDRhlZknOuU996E9jlIiUWHekns6STbv586xVtKhfjWZ1qxSugbIVocckGNMRXu4B/d+HivHBCVYKYhne/diQHMem4j1LzD7WlcAOJ/Hfj4eOUKNiGf41Zy0jrm4IwKKsnXy2ZR+DOiT63+H+bfDla7/+fOwIZL4AHQZDlbr+9yciJVZRJpqG5fjegOTAKzcHFHuiyczuB2o65wbnODbazOIDhXQLIgFvYmzASc6ZjncDJSIiEcY5l5b9vZkdA0Y55x4PRd8ap0QiQ/kysYy8Lom/vPYFz36Qxfbvf+afXc6lTGxRNvj7qHId6P0avH0fLHgStq+GLmO8ek4SrYYAG04wyYRzboyZDQ2cV6x6ghqjRKSky67XdOXTH3HrxBW8etsFVCxbyEdV1epB94nw3G+9xRs3vAKxZYITsOQnA28xRUvnXHZu4GnAP81sXeDnBGBOWKIrBZIa1eDZD7JY/vUePtlcg80/7+S2SZk806tV/hcXxfxh4I4df+zoYZjcE26e5+08FJFSoSgTTXlNKgWFmVUHhjjnauR6azCw0cymFnDlXHLgmg0neL873uoKERGJfBmEKC2eximRyBIXG8P//e4cTqlanifmrGXnDz/z7HVJVCpXlD+J/QysLFz1FNQ9B2Y/AGNT4eqnqfX2Q3DdJK0GjT5JeA/dTmYZxbzv0hglIpGiTtXyPNW9FTeM/4SHX/2C4ektCt9Ig9ZwzdPwykB4ezBc9YT/gUq+nHPTzSwZL8NE9rGNZtYNGANUw1ucoHEjSNol1mLU9cncOGEJj87djGMLz1zXinaJtYLT4ZYlcPTQ/x7fuhxe/YP3N25c2eD0LSIlSqHvqnMV9Au2AeSRls85t9fMNgDd8B4o5ifLOTcsrzfMLAGIV6oHEZHo4JwblP19oAZGArDMOfd94FhVvP/3N/nQncYpkQhjZtzeqRl1qpTjwVc+p9eYxYy/sTU1K5cLd2DQpj/UPhOm9YHnr6HsscNejns9LCuN9uKNX8WhMUpEIsaFzWrxx0ua8fS8dbRNqEnX5PqFb6RFD9ixGhaOgDpneeOqhFxezw0DKVtVkDJE2p9em05n1mXOl9s585QqtG1SM3idDVrwy7dbt26lXr164Bx88E+Y/0/Yuxm6vwgVcq97EZFoE+ZcIflK48Qr5zYE3i+Ik61sH1iItBEiIhIBzKyzmS3Fq0cxh+OLzT4IZJlZIx+60jglEqF6tGnI6BtSWLNtP11GLmLzrh/DHZKnyUXQayocO4zhIPNF2L893FGJvzLx6lecTCowt5j9aIwSkYhyR6dmnJcQz0OzPmft9v1Fa6TTw9DsMm9X04b5/gYoEiEWZe1k+eY9tKxXiTXb9nPDuE84cvRY/hf6xQw6DoHfjYLNi2HcpbB7Y/7XiUhEK+kTTSl4Dwnzshsv7US+nHN53qQFcpaPLlpoIiJSEplZJ7zVcjWAB/DqCf7COfcAsA8Y6kN3GqdEIlja2XWZ1L8te386TOeRi1i1dV+4Q/KsnPRrbYmjh+CDR8Mbj/jtMaCGmU0O7LL9hZlVNbMpeKmF8kuvlx+NUSISUbLrNVUuF8cfJq7gx0NHCt9ITCx0GQu1mnk7hHefaL5dgsHMOpnZYznHNzNrbGbvmNnRwEt/2ATRoqxfazL9p3Mzuqc0YFHWLq4f9wmHQznZBNCyJ/SeBT/s8FJDf7M0tP2LSEgVeqLJzJYW8LXEh/iqn+S9vUB8URsOpHnY65zTXx0iItFlMF6an6acOCXQXPypOahxSiTCJTeKZ/qg8ykXF0P30R/z0brvwhvQ/m2wcuLxue4zX9KupigSSB80Bi913Z7Aw7cpZvYOsAdIBzKcc2OL2ZXGKBGJONn1mtZ/9wN/efWLojVSvir0fNn7flIPOPi9fwFKfgYCA7LTlgfMxdupOw9YCQw2s3vCEVxp8NmWfTzT69eaTEO7NqdXmwYs3rCb21/ODP1kU+ML4ea5UK4yPH8VfPFKaPsXkZApyo6m5AK+Uk7UgI9OdvOUn8FK8yAiEpUKkm5oN8WvfVEQGqdEIkDTOlWYcUs7GsRXpO+EpczK3Bq+YOYPA5frAcCxIzB7SHjikaBwzg3Em2jahJfCLj3wdSOQ7py7JQRhaIwSkRIpu17T9OVbmLbsm6I1Ep8A3V6A3Vkwox8cO+pvkHIix92LmVkXvPuu6c65S51zyXhj3aATXC/FNKhD4i+TTNke7dych357Fm+v2sYfJq7g0JEQTzbVagY3z4NTW8C0G2HBk14dJxGJKnGFvcA5d8LJKTNrgjdYdHbONStOYGZWnBuf/NpOwlvFl995A/CK6FKvXj22bg3NQ4cDBw6ErK9Q96fPFpn9RWtfoe4vmj9bCbOC/Bc7pHLymhP5Cvc4Fa4xCvR7E4l9hbq/SP1sT13TiCFvbuTOKStZv2UHPZPqBK2vE6m9cSFlc+5mCjj21Vv8d8s3YMHLfB3N/0ZKopyF0c2siXPOt+IF4R6jAufpXiqC+wp1f/pskdlfMPvqemZFPlpTmYdmfc4pZX+mbvljhe+rbCKVzn+Q6gv/xv5Z9/J923sLfKnGqSKrzvH1AdMAB0zJcWwF0CWUQQncfFECcTHGI6+v5paXlvPs9UmUi4sNXQCVakHv1+DVW2HuI15ay98+8Wu6aBGJeIWeaDqZwM3RYDNrZWb3OOf+VYy29ppZ/icWzRC83Oj5xZBBIO1SSkqKq1evXrDiOc7WrVsJVV+h7k+fLTL7i9a+Qt1fNH+2EmYq8JiZ9SPwAC8nMxsFNAH+WZxOwj1OhWuMAv3eRGJfoe4vkj/by4Pqc/fUlTyz8FsOWjkevPIsYmJ+/V0P+mf74yf/21fmS8S8+gfqbZsLKX2D1nU0/xuJALvMrLFzbpMfjYV7jArEoHupCO4r1P3ps0Vmf8Hua3SfWlz59Ef8be5WRnZuUrS+6t0DP2+lyrJxVElo49WMKQCNU0W2l+N3zKYGvubMOFGdAixYEP/deEETYmNj+POsVQx8cTmjrk+mfJkQTjaVKQ+dx3o7Dj8cDns3ezsPy1cLXQwiEjTBWhI5B+gRpLb90NU5V6yV7CIiUjI554YB7+E93FqGt4Iu3cxGmtkuvNXV032ofRFMGqdEwqR8mVj+3TOJPuc3YuwCb3dTyNOL5NbyOmh8Ecx52KvhJBHDzDqbWcuTvN/SzNbh1WbKMrNdEVAkXWOUiIREznpNT8wvxu6iK4Z64+jrt8M3S/0LUPIyDRhgZo+a2RR+TZuXs2ZTCt59moTBDec14rHO5zJ/7Xf0f2EZBw+HOK1kTAxc8hBc+yxsWgDjLoU9X4c2BhEJimBNNCUCST60sxeoeYL3cm/HLRAz64pWToiIRDXnXBreiuuagOEVpR2Y/b1zrrtPXWmcEolCsTHGI9f8hvsvP4PXPv2Wm55byv6Dh8MXkBlc9RQcOQizHwhfHFIoZtYK74FbngW2AnUrluPdO2UCM/DGqcFmNtuHEDRGiUjEy67X9NaXu4terym2jLdromo9mNwL9m3xN0jJ6X5gJfAAXv3BDUD/7DfNrD/eGDQ0LNEJAD3bNGRol+YsWL+Tm55byo+HjoQ+iFbXwfUzYf9/YWwn2LI89DGIiK8KPdEUWBF+stcUvEHEjxuQuZy4WHsC+Rd7z0saRbipEhGRyOKcG+aciwdqAMlADedcvHNujI/daJwSiVJmxq0XN2V41+Z8vGEXPTIWs2P/wfAFVKsptL8PvngF1r4TvjikMLInmPrnfsPMqgHZ41Gacy7FOdctMG69B6QFUsAWh8YoEYkKd3RqRlL9yvz51VWs3b6/aI1UjIeek+HwT95k06Ef/Q1SAHDO7XPOJeMtokh2zjXNtZtpKt649154IpRs3VIa8K/0FizesIu+E5Zy4OcwTDYldIB+c6BMRXjuSlj9auhjEBHfFGVH08B8XukEVuL5EN9STn5zVJTp7vwKxIuISBQJ3OxkOuf2BaF5jVMiUS49pQFj+6Sw4bsDdBm5iM17wjjZdMEdUPtMePMe+PmH8MUhBZUEbMj1gC1bN7wV3cOcc/NyvZd9P5VezP41RolIVIiNMR65tBGVy5Xh1okrir77os6Z0HUc/PczePVWcM7fQOUXzrmNzrnMPI7vy2PckzDpnFSfJ7u3ZNnXe7hxwhJ+CMdkU+0z4OZ5cMq5MLUPLByh302RCBVXhGuSC3DOBp8e6GUAQ82sunPulx1SZpYAxOOthCDH8epAinPuZKvzElAuWBGRiGdm+RYiz4dzzj1YzDY0TomUAh3PqMPLA87jpueWcsv0dTxXrSYtG1TP/0K/xZWFq0fA+Mvg/Ufh8pJeyqfUS8CrXZuXdLwaglNyv+Gc22tmK4DWxexfY5SIRI2alcowokdLrh/3CX+e9QX/6taiaA2dfhmkPgJzH4Y6Z0OH+/0Ms9Qws0sKcfpuTrzwQsLs2pb1iIuJ4fbJmfQe9wnP3dSGquXLhDaIyrWhz+vwyiCY8xfYvQGufNxLeykiEaPQE015rUgIlsBN1mC83K0Dc7w1FBic84YpYB6QZGZpJ7lBCsNTARERCYLi7px1QLEmmjROiZQeLRtUZ8Yt7bguYxE9Mxbz7PVJdDyjTugDaXgepNwEn4yE5ulwWqvQxyAFtQFvQicvqcAe59zKYHWuMUpEos0FTWtx+yXNGDFvHeclxJOe0qCIDd0BO76E9//P201x9rX+Blo6zMW7nyowM5uDVy/36+CEJEX12+anEhsDt03K5IZxS3jhpjZUqxDiSZ4yFaDrBHgvARY8AXs3Q/pzUL5aaOMQkSIryo4mzKyxc27Tid4DEvzKt+qcG2ZmA8xsKJCFl+d1inNueh6nzyX/wrYbgBV+xCYiImFVkB22QadxSqT0aFKrEqO6NmPI7G+4+fllDO3SnK7J9UMfSKeHYc2b8Nrt0P99iC3Sn/QSfJlAZzNrlPOhWqAQOuTaUZRLAt6YUiwao0Qk2tzeqRlLNu7mz6+uokWD6pxet0rhGzHzdggwPb0XAAAgAElEQVTvzvJ2UNRoAqc29z/Y6DaGgk80xeONa5cCG8ysq3PulaBFJkVy+TmnMvL6GG6duJzrx37Ci/3aUL1i2dAGERMDqQ9DfBN44y4Yfzn0mgrVizipLCIhVei7UjPrAkw1s3Tn3Mw8TkkDRplZknPu02JHCDjnMgp43mDyWeHunEv0IyYREQmvUO6wzY/GKZHSo2alMkwecB6DXlrOvdM+Zfv3B7n14kTMLHRBVKgOVwyDaX28nU3t/hi6vqUwBgNdgDlmNhCvJlI3YDTew7mheV1kZq3wJnxOlsKuwDRGiUg0iY0xRvRsyZUjFnDrxBW8dtsFVCxbhAUXZcpD95cgoyNM7uUt3Khc2/+Ao5RzbmD+Zx0vkLp1GjDdzBJPtIC9KMzsfrzFFNm1CUefYFGFnETa2XUZfUMyg15cQa8xn/DSzW2JrxTiySaApN5QvSFM6Q1jO0HPyVAvKfRxiEihxBThmiF4uVXzmmTCOTcG2Bc4T/6fvfsMr6pK/z7+XWmEkpCECEgEIQkiCAgBQQFFIWEUK5AAllH/gwJ2xxbr6OOMBVDHihAcy4yoVAt2IooiUoOAgCIERRBQSgi9JOt5sU8QMCFt5+xzkt/nuvYVOGWt+yjJnbVXuUVERESkWomKDOeVq7tw0alNGPXJDzz03jIKCv1ctLjNxXDSeU6tpm06gSYQWWtzgeFAMs6k0TacSSaAgce4wTYCZyJqbAnPi4jUaA2jInlmcAdW/76TB95ZVvGGohrDpW/Ars0w4Qo4uM+9IOVPfHmxN849Q9eKYxljxgKTrbXDrLVpOIsmxhljJrnVR03S6+RGjLuqM6t+38ll4+awZadH3xeJZ8OQTyGsFrzSF1a8700cIlJmFZloSqH04xIWECBHGomISM1kjGlujLnDGDPBGPOJMeZFY8wQr+MSkeohIiyEpwd14NozW/DaNz9z05s57D1Q4L8AjIG+owADH9wO1s8TXVImvt1EnYAncGogjQOSrLVTinu9bzdTIpDl5kpvEZHqpqhe05ScdUxa8EvFG2rSES4ZDb/MgfdvUz6tYr76gFk4pyFVmjFmKDDCN4lV1EcOkAGkG2PS3einpul50nG8fNVp/LRlF5eOm8PvOzyabGp4MlzzGTRq40wGf/OCvkdFAlhFJprKIo8/tquKiIj4lTHmRZxaFCNwBhlpOIXQs4wxmzXhJCJuCAkx3Hd+G+7r25oPl27kqpfnsX3PAf8FENMUej8Aq6bDsmIPG5AAYK1dZK3NtNb2sdYOt9auKeW1ydba6/wZo4hIMLq5d0vOSGzAA+9+x8pNOyreUNv+cNZd8O3rMGc07NhI/LQrYccm94KVw23BvXuGSYdPMhWx1mbj3Jss9xF/4ujRMp6Xrz6NX7buYXDWN/yWv9ebQOo1hKveh9YXwif3wod3QN46fY+KBKCKTDQtAlJLeU0qLp0pLiIiUh7GmDE4AwoDjMJZSR7r+/oSTjHaLGNMP8+CFJFq5dqzEnlmcAdy1m5j0Nhv2LjdjwPxLkOd1dgfZcKebf7rV1xljOlgjIn2Og4RkWBSVK+pXq1wrh+fw+79Byve2Nn3wMkXwKf3w3s3E7FxIcwstpSeVF4apZ+UVFZ3HeOIvAVAZ5f6qZG6JcXz6v+dxobtexmcNce/v+MeLqIOZLwG3W+B+S/By3/R96hIAKrIRNNjQKwx5q2jB0PGmGhjzASgPk6BPxEREX8biFPbItVae7dvdfh239dhQB+cSSjVEhQR11zcIYFXru7CL1t3M+DF2az6rRIrq8sjJBQufAZ2b4XpD/qnT3GVMaYFsJDSF/OJiMhRDq/XdP8732EreqxWSAj0GwsNWsKPn2Cw8O147ZhwmTFmAE6+m+BSkzlATAnPxQFbXeqnxuqa2ID//q0Lv+3Yx6Csb/g1b483gYSEQNrDkPr/IH+d8z266HV9j4oEkHJPNFlrJ+OcLT4Q2OarezHBGPMJToHbDJwzxV9yN1QREZEy2QpkW2tnFPek7xiFz1AtQRFxWY+W8UwYdgb7DhaSPuYbFv7sp3sbx58KZ1wPOa/BT1/7p09xm/E6ABGRYNU9OZ5berdkas56Ji1cV/GGatVzcmoRW6gdEyXwLTQv69XcGNPftzB9IrDQWvuEG3FYaztZa0uq91SWGvNSBp2bx/HfIV3YunM/g7K+4Zetu70LJm8thIQ5fy7YB+PT4YBHk18icoQK1WjyrQgfCPyEs+W1qP7FGiBDZ4qLiIiHcnDO4z6W1ThHwYqIuKptQn2mXteNmNrhXDZuLtOX+2mV5dn3QEwzmHYLHPSoYLOIiIhHburVkm5JDfjHu9/xw8YK7iresRFWvPfH3wv2a1dTybaV41qNc+pRBs6CvyrfwWuMSff98bGq7qumSGkWy+vXdGX77gMMzprD2i0eTDbt2Oh8TxYedkzmxiXwQlctthIJAGEVfaNvZ9NkcI57OFZRWxERET96DMg2xkRZa/80yjTG1McZ5GT4PTIRqRGaNajD5Ou6MeTV+Qz73wIe6deOS7s0q9pOI+rC+f+G8QNg1r/h7Lurtj8REZEAEhpieHpwB/o+M4vrxy/kvRt7ULdWOW95zRzp7GI6XNGupgueci/Y6iEf57jystgK5AJjrbVTqi6kI4zAOW2p2B1NxpihwFCAhIQE1q9f76ewYNeuXX7rz+2+4kPg6YsTufXd1aS/OIvn+iVzQkytKuvvaPVnPUzdwoIjtoFbE4rduZmQV/uys/Vg8rvcho2o53rfwfz/LZD602cLvr7Ko0ITTcaY5tban4r+fvgkkzGmOZBY0pFFIiIiVWwozhFEOcaY7GKeH+j7mmGMOXqyyVprr6/S6ESkRoivV4s3rj2d68fncM/UpfyWv4+beydjTBWekNYyFdqmw1dPwin94biTqq4vERGRANMwKpJnB3fg8v/M5YF3vuPJgaeWL++um+fsYjpcwX7ncTmCtTbW6xhKYowZAeT6TmMqlrU2C8gC6Ny5s01ISPBXeKxfvx5/9VcVfSUkwFuNGnH5S3O4+d1c3rz2dBKPq1dl/R1h2zIoPHDEQ8YWYBo0hxY9qTfnReqt/wou+Dec9BdXuw72/2+B0p8+W/D1VR7lnmjyFe6baIzJsNZOLeYlacAYY0yKtXZxpSMUEREpn6IBRQyQVIbXHc4CmmgSEVfUrRXGS1d15u4pS/l39ko27djLPy9uS2hIFU42nfsYrMp2jtC7+gOncLIEuq04x77meh2IiEiw6+ar1/R09o+cntSAgZ2blv3Nw2cd+mOg3sSTYzPGpADpqB5vlWrTJJo3h57O5ePmcuFzs/h/F51C+mHfa7NXb2bJuu0M73ms4XgFlPY9ekp/eO9GeGMgtMuAcx+HuvHuxiAiJarIyPMenJUBxU0yYa0dB2z3vU5ERMTfOlXi6uxBvCJSjYWHhvBERnuuPzuJN+au5brXF7L3QEHVdVivIfT5J6ydDYv+V3X9iGustduttZ2ttd96HYuISHXgSr0mCTrGmBhgHNDJWltazV6ppJMbR/PW0NMJDQnhzslLmLjgF8CZZLrxjUW0P6G+/4NqehoM+xJ63g3L3oEXusDSyWDLesqjiFRGRSaaUnBW3B3LArR6QEREPGCtXVSZy+v4RaT6McZw17kn89CFbZi+YhNXvDSXvN37S39jRXX8K5zYA6Y/ADt/q7p+pMoYY3obY170Og4RkWBUVK+pXq1wrh+/kF37DnodkvjHJCBDk0z+07JRFFOv70b92uFkTl7C45+t5cY3FvH8ZR3pluTRTqKwWnDOPc6EU2xzmDIE3hwM2wOvno1IdVNVZ2nkAYlV1LaIiIiISNC5unsLnr80hSXrtpM+5hvW5+2pmo6MgQufhgN74OO7q6YPqWop+IqUi4hI+RXVa8rdvIsH3vkOqx0N1ZqvLlOmtTb3qMeVS6tYcsN6vH1Dd+rWCmXa8q20OT6a01s08DosaNQGhkyHvzwKuTPhha4w/z9QWOh1ZCLVVkUmmhYBqaW8JhUorgC7iIiIiEiNdX7743ntb13YtH0vA0bPrrojfeJbwpl3wHdT4MfpVdOHiIhIACuq1zR10XomLVjndThSRXyTSdOttcWdvhTj73hqog3b9xAWGkLTmAhmrdrMxS/MYlP+Xq/DgpBQOOMGuP4bSOgIH9wGr10Am1d5HZlItVSRiabHgFhjzFvGmOjDnzDGRBtjJgD1cbasioiI+J0x5jFjzBZjTMExLp2hISKeOCOpAROHn0GhtaSPmc3c3C1V01GPWyG+Fbx/G+zfVTV9SImMMQOMMfMrcgHaiiYi4oKiek0PvPsd32/M9zoccZkxJhXIAFKMMXcddY0AkjwOsdorqsk0+vIU3ryiNUN6tGDp+nx6P/kF05dv8jo8R1wLuPI9uOg52PgdjOkOs56GAt0SEHFTuSearLWTcYrrDQS2GWM+McZMMMZ8AmzD+QGfZa19yd1QRURESmeMGQPcBcQCa45x/eRRiCIitD4+mqnXd6NhVC3++vI8Plq6wf1OwmrBhc/A9rXw+aPuty/HZK2dgpOLOlXgivUgZBGRaqeoXlNUZDg3jM9RvabqZxLOqUojirnuAlZ7F1rNsGTd9kM1mYwxPHBBG55Ib0/diDCu/e8C7nt7KXv2F3gdpnO0dMqVcMNcSE6F7AfhpV6wYYnXkYlUGxWq0WStHYYz0fQTkIYzuZSGc+Muw1p7nVsBioiIlNNAnFqBSdba5GNdXgcqIjXbCbF1mDy8G22bRHP9Gzn895uf3O/kxDOg09UwZzT8+q377UtpsoBt1tqQ8lxoR5OIiGsaRkXy7KUdWLN5F/erXlO1Yq2NtdaaY1wjvY6xuhveM4luSfFHPJbeuSlfZp7D0LMSGT93LRc+P4tlv273KMKjRB8Pg16HjNcgfwNknQ2fPQwHAuCoP5EgV6GJJnB2Nllrk3wDoSTfoCjZt3JPRETESxOttWu8DkJEpDSxdSMYf83p9D65If94dxmjPvne/RtgqQ9BnXiYdouOCPG/hUCMMebEcr5Pd0FFRFzULSmeW3qfxNuq11SlfEfA3n50qQ2peWqFhXJv39a8PqQrO/Ye4JIXvmbcl7kUFgbArzjGwCmXOLubTh0MXz0JY3rAz994HZlIUKvwRNPhiruZp6QiIiIeyQbivA5CRKSsakeEMuaKTgw+rSkvfL6aq1+Zx4GCwkPPz169mTEzK3HyS+1YOG8EbPgW5mW5ELGUQy5gKH+NiO2+S0REXHJjr2S6J6teUxXrBIzEKbUxzxgzRPcHa7YeLeP5+JazOKdVQx75cAVXvTKPTfkBsnuoThxcMhqumAoH98Er58IHd8C+HV5HJhKUXJloKmKMiTbGXOMrYLvVzbZFRETK6G4gzRgzxOtARETKKiw0hMf6t6NfxwRmrtxMxpjZ7DlQcKjAcvsT6leug1P6Qcs+MONfkPeLO0FLqay1a3wnP8wo5/uyrLVaNCEi4qLQEMPTgzoSXVv1mqpQLHAdMAPojO8IWWPMx8aYfp5GJp6JrRvB2L924tF+7Zj/01bOffpLpi/f5HVYf0juDdd/A12Hw/yX4IXT4cfpXkclEnQqPdF02OTSJ8A2YCzOCgZXJ7FERETKwlqbizOgyTLGFBhjfvQd4XD0Nc/rWEVEDmeM4d+DOjCkR3O+/WU7g/+3ghvG5xwqsFzJxuH8JwELH9wOqk8hIiI10HFRtXhmsOo1VRVr7XbfYok0jpx06gNM8Y3P3jLGnONpoOJ3xhgu69qM9286kyYxtbn2vwu47+2l7Nlf4HVojlr1nBMAhnwKEXVhfDpMHQq7tngdmUjQqNBkUAmTS2k4x0J8BmT4ajeJiIj4lTHmceBOnJxUdFxRpxIuEZGA88AFp9C33fFs3nWQE2LrVH6SqUhMM+h1P/z4CSx/x502RUREgozqNfnH4ZNOvnuEnYBxQAaQbYzZYowZXYE6hhLEkhvWY+r13Rh2ViLj567lgue+4rv1AXRacNMuMPwrOOsu+G4KvNDF+apJaZFSlWsyyBjTv4TJJYARQKy1to+1doq7YYqIiJTZUN/XdN9xRSVdoZ5GKSJSgtmrNzMndwutG9Vm6frtvPr1n8qhVlyXYXD8qfBRJuzJc69d+RPfjtrbvY5DRET+TPWa/McY08sY8yIwEWesZnAmnGYAw4Fc3y4n1XKqIWqFhXJP39aMv6YrO/cdpN/orxn3ZS6FhQEymRNWC3rdB0NnQkxTmPw34qbfCPm/eh2ZSEArdaLJN7k0wRhTAEziyJ1Lw4Bk39+nW2sDaApaRERqqBhgsrV2qteBiIiUV1FNpucv68izlyQTXzeCh99fzhc//OZOB6FhcOGzsOt3yH7InTalJEk4Y6U/McbcaYzZ7Od4RETER/WaqpYxpoMx5jFjzBZgOs79w+3AMN+iv+HW2gyc4/XuAQYC2d5FLF7onhzPx7ecxTmtGvLIhyu46pV5bMrf63VYf2jcFoZkQ59/UWvdN/BCV1jwChQWeh2ZSEAqcaLpqMmlDJzJpCm+PxftXBoH6LBKEREJJIu8DkBEpKKWrNt+qCZTnYhQnhzUgUILWV/mutdJkw5w+vWw8BX4+Rv32pXyaIBzc01ERDyiek3uM8bcYYz5EVgIZOLcSxwFJFlrO/vuIx7iO15vJE6NXR1tXgPF1o1g7F878Wi/dsz/aSvnPv0lny7b6HVYfwgNg2438Vv6O86pAO/fCv+9CLas9joykYBzrB1NGb6vk4EU34qDgdbaKdq5JCIiAewaINUYc6rXgYiIlNfwnklH1GTqedJx9O+YwLw1W1mxwcWjfc6+B+o3g2m3wMF97rUrIiISRA6v1zRxwS9eh1MdjMTZ0VtUvz3OWnu3tba0c4ATcXY8SQ1kjOGyrs14/6YzSYitzdD/LeTet5eyZ3+B16EdUhDdDK6a5pwMsGExvNgNvn4GCrQbUqTIsSaaFuGsPEgHJhljHtVNOxERCQIDgTVAjjFmnjHmxRKu0V4HKiJSFg9c0Ib6tcO5e8oSCtw6u75WPTj/Sdj8gzNIFhERqaFu7JVMj+R4/vHuMtVrqrxMKla/fRjQoopikiCR3LAeU6/rzrCzEnlj7loueO4rvlsfQPOPxkCnq+CGuZDUC6b/A17qDRuXeh2ZSEAocaLJWtsJ5ziH63BWFdyNc9NuizFmtDGml59iFBERKY9MIAVnsURnnEFLSZeISMCLrRvBgxedwuJ123nl69IWBJfDSX3glP7w5SjY/KN77YqIiASR0BDDvwd1ICzE8H+vzD+iXtPs1ZsZM1NHZJXDQiowYWStXaPTkwQgIiyEe/q2Zvw1Xdm57yD9Rn/NuC9zKXRrsZUbopvA4Dcg/RXIXw9ZZ8OMf+mUAKnxjrWjqeis1CxrbWf+KND3EzAcmO6r4TQRsL5LRETEa53KeHX2KkARkfK6sP3x9D65IU98+gNrt+x2r+FzH4fw2jDtVlBtChERqaGOi6rFrWkt2bB9L8P+txBrLbNXb+bGNxbR/oT6XocXTCbj1FsSqZTuyfF8fMtZ9Dq5IY98uIIrX57Hpvy9Xof1B2OgbX+4YR60y3AWbo3pAWvneh2ZiGeOOdF0uKICfb6dTkn8MemUhrNqPNsY85Yxpl+VRCoiIlIG1tpFZb28jlVEpKyMMfzzkraEhYRw79tL3StYHtUI0h6Gn2dRZ+VUd9qUw8UZY6KPvoAYAGNMVHHPH/Y6ERHxk2vPTCK90wnMWrWZu95fw41vLOL5yzoeUTtRSjUJ6GSMOdHrQCT4xdaNYMwVnXisfzsW/ryNs0d9zrOfHbkL3/Ndh3XioN8YuHwKHNgDL/8FPrwL9u30LiYRj5R5oulwvi2tI621STiTTqNw6mEMBCYbYwpU+0JERLxmjGlujOlvjHnMGHONMaaD1zGJiFRUk5jaZJ7bilmrNjN54Tr3Gu54JTTrRv25o2Dn7+61K+DUu91WzHWt7/m8Ep7fBmz1d7AiIjXdiAHtaRpXm9k/5XNF12aaZCq/u3DKb0zXZJO4wRjDpV2a8f7NPWhUP5Knpq9kyKvz2XugMLB2HbZMheu/gS5DYV4WjD4dVmV7HZWIX1VooulwvkmnTGttMs6k0xM4O51U+0JERDzhWwk+AViNs6ouE+cIh4W+3bdaJS4iQenyridyWvNY/vXBCn7f4dI58CEhcOHTmAO74ZN73GlTwLnRVplLFelFRPxs7pot7Nx7kKtPa8Trc9cye/Vmr0MKNtfilNhIBnKNMfONMS8Wc2lxupRL0nH1+PTWnlzQ/ng++/43+r2yjKH/XcjzlwbQrsNaUdB3JPztY+do6tcHwNvDYbfWDknNEOZmY9baNTg38zKNMR3dbFtERKQcZgApOGeETwdygUScnbcDfc+d5Fl0IiIVFBJieKx/e/o+8xUPvbeMFy5Pcafh41qxo8NQonNGw6mDITnVnXZrMGttrNcxiIhI2RXtjnjh8hROjNxHnw7NdXxe+Y087M+GP+rjHs0C1/slIqk2IsJCeP6yFMJDv+XtResB+Hf2SiIjQklpFkC/djU7HYZ95dRt+vppZ2dT31HQ5hKntpNINVXpHU0lUe0LERHxgjHmcaAjkGqtHWitHWet/cz3NQ0YDiQbYx71NlIRkYpJbliPm3sn88HSDXy6bKNr7e7oMBQatIT3b4P9u11rV0REJBgsWbf9iEmlbknxPH9ZR5as2+5xZEGlUxmvzl4FKMFt9urNzFz5O1d2bkSdiFB+2LiT/qNnc/34hazZvMvr8P4QHgm9H4ChX0B0Aky6Gt66HPI3eByYSNVxdUdTVTHGDMU5lm+17+t8a+3kCraVDgzijzPPF1prs1wJVEREAkEqkG2tnVHck9baLF9eSQPudaND5SkR8bdhPZN4f8kGHnj3O05PakB0ZHjlGw2NgAufgVf7wszHIe3hyrcpnlOOEhEpm+E9k/70WLekeO1mKofDF50bY5rjnCRxGk4OWmCt/dabyKQ6KNp1+PxlHTkxch/ndmzODeNzSE85gQ+/28CnyzZxeddm3Ny7JQ3q1fI6XEfjdnDNZzDnBfj8UXihK/T5J6Rcqd1NUu1U2Y4mtxhj7gKSfHWgsqy1mUCab8BU3rZGAIOstRnW2mHW2mG+x3U2iIhI9ZGCc1TeseT6XldpylMi4oXw0BBGDGjP7zv28diH37vXcPPuzsB39vOwYYl77YonlKNERMTfVC9Xqkpxuw5fuDyF5Eb1+OLOsxncpSmvz11Lz1Ff8MLnq9izv8DjiH1Cw6D7LXDdbGfiadrN8NqFsLW02xYiwSWgJ5qMMTHAPb4B0eEygRG+58va1lAgxVqbcdRTI3BWtYuISPWQTelHMaQAOZXtSHlKRLx0atMY/ta9BW/OW8uc3C3uNZz2MNSJg2m3QGGADNCl3JSjRETEIzOADGAKzrHlacAw3+MDgQXehSbBbHjPpD/tMOyWFM/wnkk0jIrkX5e045Nbz6JbUgNGffIDZz/xORPmr6Wg0HoU8VEaJMFV0+CCp2HDYhjdDWY/p9+3pdoI6IkmYCjFJCBrbR7OavSB5WhrhO86WjZOoXgREakeJgOdjDG3F/ekMWYM0AIY60JfylMi4qnb+pxE07ja3DN1KXsPuDRIrR0L5z4Ov+bAvHHutCleUI4SERG/Ur1c8Vpyw3pkXdmZScPPoElMbTKnLOW8Z75kxvebsDYAJpxCQqDz/8H1cyDxbPj0fngpFTYtc57fsZH4aVfCjk1eRilSIYE+0ZRGyccf5VLG1XNFR0NYa7OPfs539MOfHhcRkeDkqxUxBRhljFlpjHnRGHOH7+sWnBtv2dbal1zoTnlKRDxVJyKMx/q1Z83mXTzz2Y/uNdx2ACSnwox/wvZ17rUr/qQcJSIi/lZqvVyckyW0G1aq1GnN45h6XTdevDyF/QcL+durC7h03ByWrMvzOjRH/QS49E1Ifxny1sLYs2DGI/DFY0RsXAgzi1vfIxLYAn2iqTPOma7F2UrZ62tkoK25IiI1hu9on+FAMs4xDSN9X2OBTGvtX1zqSnlKRDzXo2U8GZ1OIOvLXL5bv92dRo2B858EWwgf3AGBsAJUyks5SkRE/M2v9XJFjsUYw3ntjmf6bT15+OJT+HHTTi56/mtuenMRa7fs9jo85/fttgPghnnO1y9HwsLXMFj4drx2NUnQCfSJpmOdG54HxJWxnc5ArjEmxhgz9PCr8iGKiEgg8hU9DwGScG6SdbLWhlhrR7nYjfKUiASE+89vQ2ydCO6euoSDBYXuNBrbHM65F1Z+BCvec6dN8SflKBER8Te/1csVKavw0BCuPKM5X9x5Njf3SiZ7+SZ6P/UFD09bzrZd+70OD+o2gP5Z0LIP4FvcdXAvvHkpbPvZ09BEyiPQJ5pKU9YCtkWvG+q78Zjl264bY4yZVEWxiYhIALDWrrHWTrHWLgIwxkQbY5r7qXvlKRHxi/p1wnn44lP4bn0+L81a417DXa+Dxu3hw7tgr0u7pSRQKEeJiIjb/FkvV6RcoiLDua1PK76482zSO53Aq7PXcNaoz3nxi9Xu1TqtqB0bYc2XRz7260J4pj280hcWvqbfxSXghXkdQEmMMWUd+JS1nVQg8/DnrLUjjTHbjDGpxZ0t7lulNxQgISGB9evXuxFSqXbt2uW3vvzdnz5bcPZXXfvyd3/V+bN5wRjTGxgDjLXWPlGOt74E9DfGxFlr8yvRv6d5yqscBfq+Cca+/N2fPps3fbWPtZyVWJ+nPv2BDvGGpjG1XOkv/PT7Oe7dwex69y629/hHudosb1/iDq9zlO+9GksFcV/+7k+fLTj7q659edFfdWGtzTLGpOHUyx0GfIZzjGsSMBDnKPPpLtXLFamQRtGRPNa/PX/r3oIRH3/PiI+/57/f/MTtfVrRr2MCoSHG/0HNHOkcWX24kHA4vj3s/A2m3Qwf3gkn94X2gyG5N47JhSYAACAASURBVISG+z9OkWMI2Ikma22eMZX/xj6snVxrbXEV3xbgDJqKK26bBWQBdO7c2SYkJFQ6nrJYv349/urL3/3pswVnf9W1L3/3V50/m0eGAYkU8/O7FHcD6b6v91a0c6/zlFc5CvR9E4x9+bs/fTbv+ho5KJ60p2by9NebePPa0ynPz6kS+0tIgI3DqTfnReqd8Tdo1rVcMZWrL3GF1znK916NpYK4L3/3p88WnP1V17686K86sdZm+BYbjMGpmXu4TJePMhepsJaNonjpqtOYk7uFxz5cwR2TFvPSV7nc07c1Z7WML9fv0ZW2bh4UHHWMX+EB57Eb58OvObB4Anw3GZa9DXXioV06tB8ETTo69Z5EPBbsR+eVR0nFCPMo/fxYEREJPCk4N76+Lc+brLW5OGeCZ1RJVBWnPCUilda4fiT39G3NnNytTJj/i3sNn3Mf1D8Bpt0CBwPgLHvxN+UoEREpMz/VyxVxxemJDXjnhu48f1lHdu8v4KqX5/HX/8zju/V+PKpu+Cx4aDs8tJ311y4/9GeGz3ImkRI6Qd+RcPsPcOlb0LwHLHgFxp0DL3SBr56EPBd/9xepgECfaMoDGpTwXAwlD3iKa6ckWyn7+eQiIhI4Eil7HjhaLmUvgn4sylMiEnAGn9aUri3ieOTDFWzK3+tOo7XqQd8n4PcVMPsZd9qUqqYcJSIinjq6Xq5IoDLGcEH7Jky/7Sz+cUEblv26nQuem8XfJ3zLum27vQ7vD6Hh0Oo8GPga3LESLnwG6jSAzx6Gp9vBqxfAotdhb4WrBIhUWKBPNGXj3EgsTnmOS1pwjHbiqPiNShER8daxbn6Vxo0bY8pTIhJwQkIMjw9oz/6Dhfzj3e/ca7jVudDmEpg5Crasdq9dqSrKUSIiIiLlUCsslL/1aMEXd57DdWcn8eHSDfR6YibPz1rP9t0HvA7vSLVjoNPV8LeP4ZbFcM69kL8e3r0BnjgJJg+BH6dDwUGvI5UaItAnmuZz7MHRwjK2M+kY7cTgHKEkIiLBJRfn+LyKSMGdG2PKUyISkFrE1+XW1JP4ZNkmPlq6wb2GzxsBYZHOEXrWuteuVAXlKBER8TtjzGPGmC3GmIJjXLrzLQGtfu1wMs89mc/vOJuLOzThrUW/c9aozxn3ZS57DxR4Hd6fxTaHnnfBTTkwJBs6Xg6rP4Px6fBUa/j4XtiwWL+/S5UK9ImmLCDFGHPEqnNjTCLO6rmJRz0eY4xJLaadiUCi731HSwUecyleERHxnyk4P9vPKc+bjDG9cW6YTXYhBuUpEQlY157ZglOaRPOP95a5twIzqjGkPQQ/fQWL33SnTakqylEiIuJXxpgxwF1ALLDmGNdPHoUoUi5NYmozKuNUXr20FR2bxfDIhyvo/eRM3lm0nsLCAJy0MQaangbnPwm3r4RB46FZV5iXBWPPgtFnwKynIf9XryOVaiigJ5qstXlAJjDiqKdGAJm+5w/3GTD96AGS73XDgLGHP26MmQSMtNZqFZ6ISPB5FDDAJGPMqWV5gzGmOc7KbMtROaEilKdEJJCFhYYwYkB7tu7azyMfLnev4ZSroenp8Mm9sGuze+2Kq5SjRETEAwNxjjdPstYmH+vyOlCR8kiOr82r/9eF8dd0JbZuOLdO+JYLn5/F16sC+HfhsAhofQEMet2p53T+UxAZDdkPwlNt4LWL4Ns3MQd2eR2pVBNhXgdQGmvtSGPMUGPMCGA1kARMsNYWtxI9mxIK21prs4wxW30Doq04q/hKakdERAKctXa7MWYgzkrrHF+eeNxa+6eql8aYaOAenNV1Bsiw1v7kUhzKUyISsNom1OfaMxMZM3M1F3dIoHtyfOUbDQlxCg+P6QGf3Af9Kz1vL1VEOUpERDww0Vq7xusgRKpC9+R43ruhB9OW/MrIj3/g8pfm0vOk47j7vJNpfXy01+GVrE4cnDbEubashiUTndMJ3hlO47Da0OYiaD8IEs+GkFCvo5UgFfATTeAMbMr4ukycVXslPT8Zd45KEhGRAGCtnXzYZFMmkGmMycG5SZaLc0ReIn/UciqaZJrichzKUyISsG5NbcnH323gnqlL+eTWs6gd4cLgseHJ0OPv8OVIOHUQJPWqfJtSJZSjRETEj7JxFiOIVFshIYaLOyTwl1Ma8/qcn3luxir6PvsVA1JO4La0k2gSU9vrEI+tQRKccw+cfTf8Mpc9s1+i7sqPYckEqNcY2mdA+8HQuK3XkUqQCeij80RERErju/GVBLyEM5HUCcjAuVmW4fu7wanplOT2JJOISKCLDA/lsf7tWbt1N//OXulew2feDg2S4f2/w/7d7rUrIiIiwepuIM0YM8TrQESqWmR4KNecmciXd57D0DMTeW/xr5zzxBeM+Ph78ve6VB+1KhkDzU4n78z/59RzGvhfSEiBOS/CmO7wYneY/Rzs2Oh1pBIkNNEkIiJBz1q7xlo7zFobAqTh1JLI9H1Ns9aGWGsH6ggHEampzkhqwKVdmvLSV7ksWXd0aZ4KCo+EC56GbT85O5tERESkRrPW5gJZQJYxpsAY86MxZn4x1zyvYxVxS/064dzTtzUzbu9J33bH8+IXq+k58nNenrWG/QcLvQ6vbMIjoc3FcOmbzqRT3ycgrBZ8ej881Rr+1885bm+/6jlJyYLi6DwREZGystZ+hlPQXEREDnP3ea35bMVv3DV5CdNu6kF4qAtrzlqcCR2vgK+fhbbpOmJDRESkBjPGPA7ciXOiBDgnTxTH+iciEf85IbYO/x7UgSE9WvD4R9/z8PvLeXX2T9z5l1Zc0P54jDGlNxII6jaALtc61+YfnSP1Fk+AqddCRD1ofSGcOhian6l6TnIE7WgSEREREakB6tcO55+XtOX7jTvI+jLXvYbT/gm1Y2HaLVBY4F67IiIiEmyG+r6m+06VKOnS3Wmpttom1Of1a7ry3791oU5EKDe9uYhLXviab1Zv8Tq08otvCb3uh1sWw9Ufwin94PsP4L8Xw7/bwvQH4bcVXkcpAUITTSIiIiIiNcRfTmlM33aNeeazH1n9+053Gq0TB+c+DusXwPz/uNOmiIiIBKMYYLK1dqrXgYh47ayTjuODm8/kyYxT+X3HPi4dN4chr85n5aYdXodWfiEh0Lw7XPw83LES0l+Bxu2cGk6jT4cxZ8I3o2Hnb15HKh7SRJOIiIiISA3y0EWnEBkWwj1TllJY6NLJNe3SIakXfPYwbF/vTpsiIiISbBZ5HYBIIAkNMQzodAIz7jibu887mXk/beXcp7/k7ilL2JS/1+vwKia8NrTtD5dPhNt/gHNHgAmBT+6BJ0+G19Nh6WQ4sMfrSMXPNNEkIiIiIlKDNIyK5P7z2zDvp628MW+tO40aA+c/BYUH4aO73GlTREREgs01QKox5lSvAxEJJJHhoQzvmcSXd57D/3VvwZScdfQc9TlPfvoDO/Ye8Dq8iqt3HJw+HIbNhBvmQfdbnKP0pgyBUS3hnRtgzVdQWOh1pOIHYV4HUJ1Za9mxYwf5+fns3r2bgoKynVl/8OBB8vPzqzg6b/rTZ6va/kJDQ6lTpw7R0dFERUUFT6FBEfG7iuYoqHk/W6tDX/7ur6S+wsLCqF+/PnFxcYSF6ddQL2V0PoF3F6/n8Y++p3frhhxfv3blG41rAWffDdkPwoppTqFgkQrSWMrbvvzdXyB8No2lRFwxEFgD5BhjFgILS3idtdZe77+w3KWxlPf9BfNnS08yXNL8RPL3HmT3/l3MX7SUiLAQ6tYKIzI89FBf+w4UsL+gkKjIcCAI8tRxrSD1Qej1APw8CxZPgOXvwLevQ/2m0C6DsMbnQEKC15FKFdEIv4pYa/ntt9/YtWsXcXFxNG7cmNDQ0DL9ENi/fz8RERF+iNL//emzVV1/1loKCgrYuXMnmzdvZs+ePTRs2DDwEo+IeK4yOQpq1s/W6tKXv/srri9rLfv372fLli388ssvnHjiiYSEaHO9V4wxPNavPX2enskD73zHuCs7u9PwGTc4R2V8eCe06AmR0e60KzWKxlLe9+Xv/rz+bBpLibgm87A/d/ZdxbFAUE40aSwVGP1Vl8+2e/9BNmzfy659BzFAXHQksZEh7C80rN26h+S42tSLDA+uPBUSAi3Ocq6+o+CHD2Hxm/D10zSyT8HsjnDqpdB2ANSN9zpacZEmmqrIjh072LVrFyeeeCKhoaFehyM1gDGGsLAwYmJiiIqK4ueff2bHjh1ER+sGj4gcSTlKvGCMoVatWhx//PGsW7eObdu20aBBA6/DqtGaNajD7WmteOTDFby/ZAMpbozzQsPhomdgXG+nXtP5T7jQqNQ0ylPibxpLibimk9cBVDXlKHFTnYgwEuPrsmPvQX7N28Om/L1s2WkotNA0rg71fLuZgjZPRdRxarm2S4cdm8j7+j/E/PShc9T2J/dCciqcOhhOOg/CI72OVipJE01VJD8/n7i4OCUd8URoaChxcXHk5+cHftIREb9TjhIvGWOIiYnRRFOA+L/uzZm25Fceem8Z/7v0JFw5yCKhE3QdBnPHQvtB0PQ0N1qVGkR5SryksZRIxVlrF3kdQ1VTjhK3GWOIrh1OVGQYP2/ZTb6vZtPaLbuJigwjtk44UbXDCfHtXgraPBXViF3triLm3Hth0zJY/BYsnQQrP4Za9eGUi52dTk1Pd3ZFSdDR/7Uqsnv3burVq+d1GFKD1atXj927d3sdhogEIOUo8VqdOnXYs2eP12EIEBYawogB7dm+5wDPzlrvXsO97ofoJjDtZigI4gLH4gnlKfGaxlIilWeMaW6M6WWMiT7ssWhjTHPvoqo85SipKrv2HWT3/gLi64YTGmKoXzuMPQcK+HnrblZsyGfdtt3s2ncQa23w56lGp0Cff8Lfl8Ff34FW58HSKfDKefDsqTDjX7B5lddRSjlpoqmKFBQUaHWDeCo0NLRcBSlFpOZQjhKvhYSEUFhY6HUY4tP6+GiG90zi4++38eXK391ptFYU9H0CflsOs59zp02pMZSnxGsaS4lUnDGmvzFmPrAamM6RdZruBVYbY070JDgXKEdJVdi59wBrt+6hWVxt4uuGc2JcHXbuK+CE2Nq0iK9LVGQ4ebsPsPr3nfywaQebdx1g3/5qsJgrJBSSzoH+Y+GOldAvC+KS4Ksn4flOznHc88bB7q1eRyploImmKhSQBdmkxtC/PxE5Fv2MEC/p31/gubFXMs1ianHv20vZte+gO42e3BdaXwQzR8DWXHfalBpDPyfES/r3J1IxxpjewGQgFrgbOOKbyVp7N7AdGOH/6NyjnxHitt0HCmgWV/tQTaZ6keE0i6vNngMFREWG0yyuDq2Pj+aE2DpEhIbw2459bMzfx4AXZ/P6nJ/J273f40/gglr14NRBcOU7zk6ntIfhwB748A544iR48zJY/i4c3Od1pFICTTSJiIiIiNRwkeGhZPZqyrpte3jy05XuNXzeSAiNgPf/Dta6166IiIgEokxgtbU2Gcgq4TXZQCf/hSQS+BpGRR6aZCpSLzKchlGRh/4eGmKIqxtB4nH1OLlxNPVrh5G/5wD3v/MdXR75jOH/W8inyzay/2A1ODkiugl0vwWunw3DZzn1X9cvgIlXOpNO026FtXM1vggwmmgSERERERE6JNTjitOb8crsNSxau82dRqOPh9QHIfcLWDLBnTZFREQkUKXiTCQdy1Yg0Q+xiFRbEWEhREWG8+nfz+L9m3pwxeknsuDnrQz930K6PprNP979jkVrt2Grw0RM43bwl0fg78vhiinQMg0WvwUv94FnO8LnjxV/esKOjcRPuxJ2bPJ/zDWUJppERERERASAzHNPpnF0JHdPWereashOf4OmXeHje2DXFnfaFBERkUCUw5E1mYqT6nuda4wxQ40x6W62KRIMjDG0TajPPy5swzf39OaVq0+je3I8E+b/Qr/Rs+n95Eye++xHftm62+tQKy80DJJTYcBLcOePcMmLENPUOab72Y7wnz4w/z9/1HOaOZKIjQud58UvNNEkASM2NhZjTKlXbm7un96Tl5dXoT47deqEMYaMjIwyvT43N5eMjAySkpIwxpCUlERGRgY5Oa7+jiQiIgFGOUpqiqjIcP51SVt+2LSDF79Y7U6jISFwwdOwLx8+vd+dNkXkCMpTIhIgJgIpxpghxT1pjBkDtADGutWhMeYuN9sT9ylH+Ud4aAjnnNyQ5y9LYf79qYwY0I7jomrx5PSVnDnycwaO/YYJ89eSv/eA16FWXq0o6HAZXDUN/v4dpD4Ee7fDB7fBk63g9XRY9F8MFr4dr11NfhLmdQAiR0tPTycuLq7E54/1XHnk5eUdShiTJ08u9fVZWVkMGzYMgJSUFFJTU8nNzWXy5MlMnjyZN998k8GDB7sSm4iIBKZgzVGTJk3ioosuciU2qf56t27Ehac24fnPf6Rvu8a0bBRV+UYbtYHut8JXTzhFfmu1rHybIvInwZqnNJYSqR6stSONMWk49ZnuBiyQYYzJAAYCscAka+1Lle3LGDMWiEOTTEEjWHNUMI6loiPDGXRaMwad1oxftu7m3W/XMzVnPZlTlvKPd5eR1qYR/VMSOLPlcV6HWnn1T4Aef3fGGhsWO8fqLXwFCnwTagX74cM7YeBrYIy3sVZzmmiSgDNu3DhiYmKqvJ+JEycCTqIrSh7p6cXvtM7JyWHYsGEkJiYyffp0EhP/OE44Ly+Pa6+9lhYtWlR5zCIi4q1gzVGHPyZSFg9e2IavfvydzClLmDy8GyEhLgzKzroDlk2F924ivlY8XPEWRDWqfLsickiw5imNpUSqD2ttmm+X0d2AAYb5nsoDhllrx7nUT1G7GN08DgrBmqOCfSzVNK4ON/ZqyQ3nJLN43Xam5qxj2uJfeX/JBuLrRXBOUjRXnlmPtgnRwf29ZAw06QBRjZ2JpiK2EFa86xyv1/FyaD8IYpp5F2c1pqPzpMYaO3YsiYmJ3HPPPQBMmFBygeqi54rec7iYmBgmTZpEx44dqy5YERGpUdzOUSkpKVUXrFRL8fVq8cD5bchZm8f/5vzsTqPhtZ0j9PLWErEpR+eliwQxjaVE5FistSOttXE4O5g6AbHW2ji3JplEjkVjqeIZY+jQNIaHL27L3HtTyfprJ05rHsc7S7dw4fOz6PPvLxn9xSp+zdvjdaiVM3OkM7l0OBMKB/bAjH/B0+3g1Qsg53+wN9+bGKspTTRJjVS0jTY9Pf1QwjjWdtqiLbedO5dW01JERKRylKMkUDjHacQz8uPvWe/WgPO4VmBCMQCLXtd56SJBSHlKRMrKWrvdWrvIWrvd61ikZlCOKpuIsBD6nNKYF6/oxHtDTuGRfm2Jrh3OyI9/oPuIGVw2bg6TF65j576DXodafuvmOcflHc4WQL3j4JbFcM79kP8rvHcjPNESJg+BH6dDQRB+1gCjiaZqZszM1cxevfmIx2av3syYmS4Vc64msrKyABg0aBDAoS20JSWfolUNRdtvRUSkYpSnSqccJYHCGMOj/dphgfveXoq1tvKNzhwJIUVDEKtdTRJwlKdKpzwlIuIN5ajSKUeVX3RkGJd3PZEp13XjizvO5uZeLVm3bQ93TFpM539N59a3FjFz5e8UFLowFvCH4bPgoe3w0HbWX7v80J8ZPgtim0PPO+GmhTAkGzpeAauyYXw6PNUaPrkPNi71+hMELU00VTPtT6jPjW8sOpR4Zq/ezI1vLKL9CfU9jiywTJgwgZiYmEOrG4oS0NixxdeQzMzMBGDYsGGHkpaIiJSf8lTplKMkkDSNq8MdfVrxxQ+/8+63v1ausR0b4dvxRxbm/Xa8djVJQFGeKp3ylIgYY66p7OX1ZwhGylGlU46qnObxdfl72knMvPNsJg8/g/4pJzDj+9+46uV5nPHYZzzywXJWbKgGx80ZA01Pg/OfhDtWwqDXoWkXmDsWxvSA0d3g62chf4PXkQYV48rKxBqgc+fOdsGCBWV+/YoVK2jdunWJz/+/actY/mvx35jW2koVX9u+5wCrfttJo+habMrfR3LDetSvHV7i6yvaX5sm0Tx44Snles/+/fuJiIgo9rnY2Fjy8vIYOnRoicUB09LSSE1N/dN7tm3bVux7iusvNzeXpKQkhg4deijR5OXlERsbC1BiW5MnTyYjI+PQ31NTU8nIyGDgwIHExMQc87NVhbL0V9q/w7Jav349CQkJlW4n0Pryd3/V+bMZYxZaa2vWXvMA4naOgsDJU5Xpy808Few56lifrSr4M0dB9f1ZHih5o6DQMuDF2fy8ZRfZt/WkQb1aFevg/dtg0f+OPMoiNAI6/hUueKqCUZeN8pS3/JmnKpujIHDzlMZS7qmuYyl/91dd+/J3f8GYo4wxhUDRDcXDfwiW5SajAay1NtTFeCyQYa0t+Yy0I18/FBgKkJCQ0Gnu3Lll7mvr1q20atXqmK955MMfWLFxR7HPVTZP5e85wKrfd9Ewqha/7dhH8nF1ia6CHNW6cRT39T325zxaYWEhISF/3tPQqFEj8vLyGDJkSIk5qnfv3vTu3ftP79m0aVOx7ymur9zcXFq3bs2QIUMYPXo04OSoRo0aAZTY1tSpU7n00ksP/b1Xr14MGDCA9PT0Q68v6bNVhbL29cMPPxAXF1fp/nbt2kXdunVLfH7fwUJm/5TPJ99vZfbP+RQUQnKDSM49OY60VrHE1y35nnN5+3JbefsL2ZtH7dyPqPPje0T8thhrQtjX5Ax2n3QRe0/sjQ2v41pfleHv/44nnHBCmfJUmD+CEf+qXzucRtG1WJ+3l4SYyGNOMgWi0lYQHD44qoii7bKHD3RiYmJITU0lOzubiRMnMnTo0D+9Lz09ndWrVzNixAgmTpxIdnY22dnZZGZmMm7cOC666KJKxSUiUlMEc54K1hxVdGSESEWEhhhGprfn/Ge/4uH3l/PM4I4Va6i489IL9juPiwQQ5amSaSwlIkfJBSYDW70OpDystVlAFjiLIcozqZifn1/qRHVIaMgxJ3gqM9FUv04EjaIP/pGj6hw7lor2FRIaUu4FAKVN4v/nP/8p8bnQ0FDOO++8Pz0eERFRbJvF9fXee+8BMHjw4EPPNWzY8FCOeuedd4rNUYMHD6ZLly6HctSMGTOYMWMG991336GxVKAt2gMICwtzZUK8LBPriSfCFT1h6679vL/kV6bkrOf5r39l9Oxf6dHyOPp3TKDPKY2oE3HsqYbAXzSQAEmnQNodsHkVZslbRC6eQOTnmRBRD1pfBKcOhuZnHnYceEX7qjh//3csM2utrjJcnTp1suWxfPnycr3+cPv27avwe6219utVv9uOD39qn/zke9vx4U/t16t+r9L+yuNYfcXExFjAbtu2rcztlfae4vpLTEy0zj/9I40dO9YCNjU1tUx9L1y40N51110WZ8WOnTNnTpnjdkNZ/r9V5t/h4datW+dKO4HWl7/7q86fDVhgA+BndU29/JmjrPVvnvJnjjpWf8GeoxYuXBgw+b6IWznK2ur7szzQ8sZTn/5gT8x8385YsanK+3Kb8lTNyVNu/KwL1DylsZR7qutYyt/9Vde+/N1fMOYoYASwCigECoD5wB1Ac4/isUB6Rd6rsZR7NJZyR1n78jpPrfpthx318fe222Of2RMz37dtHvjI3jbhWzvrx9/twYJCV/uqKFf6Kyiwds0sa9+5wdpHT7D2wWhrn2xj7fQHrf3te3f7KqNAHUupRlM1U3Q+6/OXdeS2Pq14/rKOR5zfWtPl5uaSm5tLamoqeXl5R1xFq/uys7PJy8srta2UlBRGjBjB9OnTAY7YZisiIsVTnipZVeaow1eei1TU9eckkdywHve9vZSd+w56HY5IlVCeKpnGUiJSxFqbaa1NBjoBTwBJwEhgtTFmpTHmUWPMiZ4GWQ0pR5VMYyn/SzquHnf8pRVf3XUObw09nQvaN+HTZRu5/KW59Bgxg8c/+p6Vm4o/QjKohIRA8+5w8fNOPaf0l6FRG6eG0wtdIOtsmDOGkD1BtbGzSmiiqZpZsm47z1/WkW5J8QB0S4rn+cs6smTddo8jCwxF54hnZ2cTGxt7xJWUlHTodRMnTixzm6mpqaSkpLBmzZoyJSwRkZpMeapkVZmjcnNzlaOk0mqFhTJiQHs25O9l1Mffex2OSJVQniqZxlIicjRr7SLfpFMcf0w6xQN3A7nGmB+NMbcbY5p7GGa1oRxVMo2lvBMSYjg9sQEj0tsz//5Unru0Iyc3jmLcV7n0+feXXPDcV7w8aw2bd+7zOtTKC68NbQfA5ZPg9u/hL49BYQF8nEnj8WfDG4Nh2TtwYK/XkXpCNZqqmeE9k/70WLek+ENJqKYrOlO8aFXC0aZPn87IkSOZNGlSsee2liQxMZGcnBy2bt1aYmFDERFRnjoWf+Sohg0buhKr1FydTozlqjOa89o3P3FRhyZ0OrHyBYhFAonyVMk0lhKRY7HWLgIWAZnGmI7AYGAAMAoYaYzJBcYAU6y1P3kWaBBTjiqZxlKBITI8lAtPbcKFpzbh9x37eG/xr7y9aB0Pv7+cRz5cQddmUVx6hiGtTSMiw0O9Drdy6jWEM653rk3L2fn1S0St+RBWfgS16kPbftB+MDQ7HSpRly2YaKJJaoyibbTp6eklFsHt3LkzI0eOPLSdtmigk5OTQ0pKSoltZ2dnExMTQ2JiYpXELiIi1ZtylASTO//SiunLN5E5ZSkf3NyDWmFBPkgUkVIpT4lIeRw16ZQCpAID+WPSaaG1touXMUr1oRwVmI6LqsWQHi0Y0qMFKzftYGrOeqYsWMtNby4iqlYYfdsdT/+UBE5rHkdISJBPxDRqQ37X24m6ZBSs+RIWvwVLJsLCVyG2uTPhdOogiKve/450dJ7UGEXbaAcNGlTia2JiYg4lpcO302ZkZJCWlkZOTs4Rr8/LyyMtLY28vDyGDBlSBVGLiEhNUNU5qjyr9kRKU7dWGI/0a8uq33bywoxV7RcI2QAAIABJREFUXocjIn6gsZSIVJS1NgdnJ9NjwGTA4Byz5zZts66hNJYKfCc1iuLu805mytVtGH9NV/qc0phpS35lUNYczhz5OU9++gO5v+/0OszKCwmFpHOg/1i440e4ZIwz0TRzBDzbEf7TBxa8DHu2eR1pldCOJgk4pRXZGzZsGOnp6Uc8du211xb72sLCQkaNGkViYuKhbbRHv7e49rOzsxk7duyhZJKamkpWVhadOnU6YiVDUSJKTU3l0UcfLf3DiYhIUAvWHDVixAj2799f+gcUKaOzWzWkX8cERn+xmr7tj+fkxtFehyQiBG+e0lhKpPrx1WVKBwYBRVtGDM5k01gX2r8LSAOKtgiMNcZkAHnAtdZaFdUJMMGaozSWck9oiKF7cjzdk+P55yWn8OmyTUzJWccLn6/iuRmrOLVpDANSErigfRPi6kZ4HW7l1KoHHS51ru3rYelEZ6fT+3+HjzKh1XnOTqfkVAgL8s/qExQTTcaYoUASsNr3db61dnI525gE5AJjrbW5xphEnEQ3yFp77J904lfZ2dnHfD4tLe1PjxUlleLcd9995OTkkJubW6ZVCEWJKScn59B22rFjx5KZmcnYsWPJzs4mNzcXcBJORkYGQ4cOVdIRqcGUp2qOYM1RIlXhgQvaMHPl72ROWcrU67oRGuxHXlRTylE1S7DmKY2lRKqHYiaXin45mAxMsNZOcasva+1IYKRb7UnVC9YcJVWjTkQYl3RM4JKOCWzK38u7365nas56/vHuMh6etpxzTm5I/44J9GrdMPiP6q6fAD3+Dt1vhQ2LnQmnpZNg+btQpwG0TXeO1muSEtT1nAJ+osm3QqGBtTbzsMfGGmPirLVZ5WgqESfZ3WX++B+WA/R2LViplG3byr9tsLT37N+/n4gIZ1bYWlvmdot7bWJiIiNGjChfgCJS7SlP1QzKUSJ/Flc3ggcvbMMtb33Lq7N/YkiPFl6HJEdRjqo5lKdExCv+nFyS4KQcJaVpFB3J0LOSGHpWEst/zeftRet459tfmb58E/Vrh3N+++MZkJJASrNYTBBPxGD+f3v3HiTXVdh5/HckWbZkPXpGsk0kGeEeB2wT+TGSE2KyOLF6CASWipcZiTgkSxY8Q1yktmqhpiPIH9lNUkpPOexmi1DMOE52s8TEmkHOwrIsmbYTJ+AKkWaMZeMEzLR4jPAj9qhlCxvLks7+cW+Penq6e/pxH6dvfz9VXbL6cc+5o9v3N8fnZaRtN3qPt/+eNPeQ9NjnvL2c/mlc2vpG6Yb3Sbv2Sakr465t05zuaDLGpCQdsNb2VLyUlXTcGHOoiamweXnrwZam1M5aa+t3pQMAUAc5BaDbveeGbfrrR0/o7q98S2+/7gpd2bs+7irBR0YBAMJSo3OpKOkeSdN0LgFo1XXbNum6bdcp+45r9LW5F3R4dl6HZ+d139e/r51b1uv2m7br9pu2a+eWS+OuantWXyS98Re9xytFb3bTY38lPfhfpAd/T3rDz0k3/Ip03XukizfGXduGON3RJGlY0tHKJ621RWNMQdI+SQ2PxGt2iQgAAFZATgHoasYY/f7tu/T2Tz6sjz/wuP7iP/x0Z48yTBYyCgAQloIk6/85Jm/m0jfirRKAJFmzepVufeNluvWNl+n0q2f1/554Rodn5/XHDz6l/5Z/Snt29uj2/u16965t2rz+orir2551KWn3v/ceJ78rHTvkzXT633dJX/qodO27vZlOV/289PLz2vrFX5d+9T5p4xVx13yJVXFXYAUD8kKrmoL/OgAAcSGnAHS97al1yr7zGv3DU8/r87Mn4q4OLiCjAABhS0salTRjjDnXxONs3BUH0Dk2XLxGg7t36L4736KvZW/T6DvepOIrr+kTDzyhm/8gr9/87Iz+5pvP6MzZ8/rMw3N6ZO75JZ9/ZO55febhuZhq36SeN0i3jkq/NSt9MC/deIf01LT02fdK//U66bPv1dpnZqSH3Vvu0fUZTXskTdd4bUFSJsK6AABQiZwCAEnv/5md+sI3fqjf+z9P6tY3XqbLNl4cd5VARgEAwnNc3owmAIjUttQ63fXzV+s3b+3TEyde1OFH5/WFb/xQX37iGfWsv0g3v6FXn/7b7+gz79+tneu8TqaP3PeoPnXHTXFXvTnGSFfe7D3ecVD69lek2f8pfSfvbYT36P+Sbs06NavJ9Y6mVJ3XipJ6mzmYMaZfXoNr8djW2rHWqgYAADkFAJK0apXRH773ev3SH/+DfveL39Sf3NEfd5VARgEAQmKt7Yu7DgC6mzFGu3Zs1q4dm/XxX7pW//DUv+rzsyc0/eSzOnP2vN5/79fVt+USnXjxNf3Ou67VzW9o6ldft6y52NurqfB33t5O517znn84J737k7FWrZzrHU0rqdd4qpSW1GutXVyH3BiTM8aMW2tHgq8aAADkFIDucfXlG/Rbt12tP5r+tn75xmc1cJ07o+tQFRkFAACAjnfR6lW67ZordNs1V+jUK6/py48/rU//3Zyeev5lSdLHH3hC//mLT+q6bZt0w46Urt+xWdfvSCm99VKtWtUh+8u+9Iz0jb+80Ml07oz3d4dmNTnb0WSMaabh04g7rbXFiucOSjrpN5Bmq9RhWN4mutq+fbtOnGh8zfmzZ8/qzJkzLVX0/PnzLX/W9fI4t2jLO3v2bFPXbS0/+tGPAjmOa2VFXV6Sz60bxZ1TcWWUxL21E8uKurwoM0pK7r28E3Pj3/7kJXpg9hJ9/POP6fWXXKMNF68OrSzUFndG+XWgLdXBZUVdnovn1oltqajLS2pZcZQHAAjG5nUX6fVb1uv0q2f1gZuv0ANPLOjXfnanfnzmnI7Nn9L9R36g//HIdyVJGy9eo11+p9MNOzbr+itT2rb5EhnjYOfTw2OSPb/0OXveqVlNznY0WWuLQf6jVmkYlcooSDogaajK6xOSJiRpz549dvv27Q2X9+KLL2rt2rUt1fXMmTMtf9b18ji3aMtbs2aNmrluazlx4kQgx3GtrKjLS/K5daO4cyqujJK4t3ZiWVGXF2VGScm9l3dqbnzyfRv17z79Nf3FY6f0B7fvCrUsVBd3Rvmv05bq4LKiLs/Fc+vEtlTU5SW1rDjKAwAEo3xPpp2XvKq33/iGxb//zruv07nzVt957rQemy/qsR8UdWz+lO79akGvnfO2ndu6Ya2u92c9lWY/bdngwP6z8//kzWIqd+6M97wjnO1oilBBEovIAwBcRU4B6Cg3XpnSb7z1Kt371eN6zw3b9DPpLXFXCeEhowAAAOCMY/On9Kk7btItfVt14sQJ3dK3VZ+64yYdmz+lW/q2avUqoze9bqPe9LqN2rfnSknSq2fP6Z+ffknH5ot67AendGy+qL/91nOyXt+TtqfW6cYrLyy5t2vHZm24OOJulQ9/dfE/XR0M4XpHU1FSrZZpSl7DZkXGmElJR2psVtv0RrgAAPjIKQCo4qNvf6P+5slndODw4/q///Hf6JKLqi+hh1CRUQAAAOgqH761b9lzt/Rt1S19W2t+5uI1q3XjlSndeGVK+lnvudOvntUTJ04tdj49Nl/Ulx5/WpJkjNR32YYls542Vy5r14Vc72jKy9t4tpq0/3ojBiUt1Hm9oUYWAAAVyCkAqGL92jU6ePv1ev+9X9d/f/Apjb7jmrir1I3IKAAAAKAFGy5eo7ekt+gtZaszvHD6VR07cUrH/FlPf//t53V41tvPb80qo2t+4ru6YUfK63y6crOuvmyD1qxeFdcpRM71jqYjkvbXeC0tabLB44xZa7M1XstIOtRsxQAAEDkFADX93E9u1eDuHRr/+4Ledf1P6M3bNsddpW5DRgEAAAAB2bLhYv3Cmy7XL7zpckmStVZPn/qxjs0X9dV/nleheE5f+MYP9Zdf/74kad1Fq/VT2zct2fNp55b1CnIvVZe43tE0ISlnjEmVb0BrjEnLW6JhSaPGGJOStMdaWzk6b84Yk7bWFire3y9v2YhaDScAAOohpwCgjt9517X6u289p9/+/ON64K5bumpEnwPIKAAAACAkxhhtS63TttQ67eo5r+3bt+v8eavjL/xoyX5Pn/3H7+nVs97SepvXXeTv9eTt93TjlSldsemSmM8kGE53NFlri8aYrKScpJGyl3KSsuUNJt+DkvqNMQPlDSRr7YQxZtwYkys1kPyG1KSkkSrHAQBgReQUANSXWr9Wv/ueN+sj9z2qP/vacQ2/bfma6QgHGQUAAABEa9Uqo77LNqjvsg26/aYdkqTXzp3Xt599ScfmL+z59JmHCzp33kqSrth0sa7fkdINfufT9Ts2K7V+7ZLjfubhOV2/Y/OSvaYemXtex+ZPVd2XKg5OdzRJkrV2zBgzbIzJSZqT1CfpfmvtVJW351VjY1tr7YgxJudPTUvJG8U3ZK2dDa/2AICkI6cAoL537foJ/fW1P9Qnp7+tX3zz67Rzy6VxV6lrkFEAAABAvC5avUpv3rZZb962Wb/y06+XJL1y5pyefPrU4qynY/OnNP3ks4uf2bll/WLn0w1XpvSmKzboI/c9qk/dcZN2XuJ1MpX+7grnO5okbxRdg+/Lqs7SDXXWFocDenp6VCxWHxDZ39+vkZERDQ8P1/x86bOpVCqU+pWU13N6elqZTGbZewqFgvr6+pTJZDQ9PR1qfQDEj5xKPjIKaJ0xRr//yz+lgU8+rAOHH9dffuhn4q5SVyGjugM5BQBwFRkFLLdu7Wrt3tmr3Tt7F5879cpreuLEKT02X9SxH5zSzHcX9MXHfihJWmWk7al1+o0/P6Kbtl+qf/nXH+vTv9q/ZIZT3DqiowndJZfLLQmPubk5TU1NaWRkROPj43rwwQeXhcvU1JSGhoY0ODioyclG9zUOpq7VggcAkExkFNCa122+RLdcvUVf+eazOnT0B/q5baslubfcA9DpyCkAgKvIKKC+zesu0luv3qq3Xn2h8+i5l36sx+dP6bEfFPXY/Cn960uv6h+/95J+7S07nepkkuhogoOGh4eXBUsul1M2m9XY2Jh2796tubm5mGp3QSaTUT6fV6FQUDqdjrs6AIAIkFFA6379LW/Qg//8nH73C9/UX/3atfqeg8s9AJ2OnAIAuIqMApp3+cZLtPfaS7T32iv0yNzzevzEKb3ruk360uNP6527XudUZ9OquCsANCqXy2l4eFiFQkHZ7NKVOwYHB2WtjXR0Q6kOlXUJysDAgPx18AEAjiOjgJW99Se3KvfeXXrltfP6rQe+s9jJ5FLjCEgqcgoA4CoyClhZ+Z5M/+nWHfrUHTfpI/c9qkfmno+7aovoaEJHyeVykqSxsbGa67tGJZPJKJ1Oa2pqKva6AADiR0YBK3vv7iv1s31b9P2Tr+oX33wFnUxAhMgpAICryCigvmPzp5YM0rulb6s+dcdNOjZ/KuaaXUBHEzpKKpVa3CBwYqKhfY1DVRrdcPDgwZhrAgCIGxkFrOyRuef1L0+/qHdf16uvfPNZp0bgAUlHTgEAXEVGAfV9+Na+ZYP0bunb6tRet3Q0JdVLz0h//k7ppWfjrkngBgYGJEnT09OLz83OzsoYs2Raa7FY1F133aWenh4ZY9TT06OhoSHl8/llnxsZGdHs7KyGhobU19ennp4ejYyMrFiX0vqyzYZgae1ZY4wGBgaW1GlkZETGmMXnjDGLD0ZSAEiMhOYUGQXUVlru4U9+tV8H9r7eyeUegEXkFDkFAK4io8gowEF0NCXVw2PS9/9RejgXd00CV9qIr1Ao1H3f3r17de+992rfvn0aHR1d3MyvPLBKDh06pL179y4ev1gsamJiouHwKRaL+tM//dOG6j8wMLAYkKU1aAcGBjQ1NSVJGhoaUi6XWzzPXC63+KjcNBEAOlZCc8rVjGq0gURGIUydsNwDsIicoi0FAK4io2hLAQ5aE3cFutaXf1t65vGqL62x5yXTRh/g2TPSD49K9rw08+deOavX1nx7y+W9bpf0zj9svZ4tKt2QFxYWar6nUChodnZWH/3oR3X33Xcvea3aKIHe3l7NzMws3tjz+bwGBgY0MTGhbDa7WGY1Bw4c0NjYmO6++27ddddddes+NjamfD6v8fHxxSnBktTX16eDBw9qcHBQmUxGmUxG999/vyRpdHS07jEBIBSO5FRbZcWQU65mVC6X0wc+8IG6dSejELZqyzrc0reVfZrQmho51XZGSeQUbSkAaA9tqZa4mlG0pYDGMKMpiU59X7LW+29rpeL3461PwEqB09vbW/M9pXA5fvz4steqjRLIZDJLns9kMos3/NLIg1pK68geP358xfcePHhQ6XRa+/btU7FYXHyUpvKuNGoDABIhwTnlakYVCgUdPny47nvJKADwkVOSaEsBgJPIKEm0pQAXMaMpLnVGBZw9c0Zr19aegVTXS89If3yDJD90ZKUfF6XBP5M2XhF8eTEo3ZzrjTro7+9XOp3W4cOH1dfXp0wmo4GBAQ0ODjZczv79+zU2NqYjR46s+N5sNquJiYnFUQrVlAdNT09P1fcUCoW65wUAkXEkp8io6lrJqLGxMb3vfe+r+h4yCkDHqZFTbecGOUVbCgDaRVuqJS5nFG0pYGV0NCXNw2Pe9Nly9ry3buu7PxlPnQJWWnO1v7+/7vtmZmb0wQ9+UIcPH9bExIQmJiaUTqc1PT3d0M299J5GNuRLp9O67bbb9NBDD2l2drbqKIpSYA4PD2toaKjqcfbs2bNiWQDQ0RKeU65mVGndcjIKAFZATkmiLQUATiKjJNGWAlxFR1PSzP+TdO7M0ufOnfGeT4jSJnwrbdyXSqX0uc99Ti+//LLy+bzuv/9+TU1NaWRkpOoGgZUaGUlR7mMf+5geeughHTx4ULnc8g0Zy4+TyWQaOiYAJE7Cc8rVjMpms8rn82QUAKyEnJJEWwoAnERGSaItBbiKjqak+fBX465BqLLZrIrFogYHBxsOhFQqpcHBQQ0ODmpgYED5fL6hz42Pj0uSdu/e3dD79+7dq3Q6vRhu1eqRSqV06NChxWMDQNdJcE65nFGZTEZXXXUVGQUAKyGnlqAtBQAOIaOWoC0FuGVV3BUAGjU2NqaxsTGl02ndc889dd9bLBYXR0KUK20sWOnQoUNLpszm83lNTEwsbvzXqGw2K0lVRziUni9tBljts+V1KG1+WBpp0ciUXgBAPDohoz72sY9JIqMAoBt1Qk7RlgKA7tQJGUVbClgZM5rgnNINv2Rubk5TU1OLG+fNzMxUXRO13NGjRzUyMqJsNqs9e/YolUppdnZWhUJBo6OjVT9z1VVXad++fSoUCoujIGoFSC3Dw8OLU2prvT49Pa2JiQnl83llMhktLCwon88vBlLp3Pr7+5XP5zUwMLD43/fcc09TGxwCAILVyRn1oQ99SJ/4xCfIKABIsE7OKdpSAJBsnZxRtKWABlhreTTw2L17t23Gk08+2dT7y7366qstf9b18uqVlUqlrKSqj/7+fjs+Pl7zszMzM1aSHR0dXXxuenra3nbbbYvHTafTNpfLVf3c8PCwnZ6etv39/YvlTU5O1q1nrXPL5XKL9c5kMlWPMT4+vlhWOp22g4ODdm5ubsl7Tp48uaQ+uVzOnjx5cll59bRzHZabn58P5DiulRV1eUk+N0lHrQP36m59RJlR1rqTG1GW1+kZVTq3JGaUtcm9lyc5N6I+N3Kqe3LKldyIuqxOzynaUsFJ6r08yT9HMqp7Mspad3IjyvI6PaNK5+ZSRlnbmTmV5Ht5UsuytvGcYkYTnHHy5MmWP9vf3y/vur8gk8nobW97m9auXdvQMTKZjGZmZlZ830r1HB0drTmKomR4eHjFKbqpVKqh+gAAwkdGLUVGAYBbyKmlyCkAcAcZtRQZhaRijyYAAAAAAAAAAAC0hI4mAAAAAAAAAAAAtISOJgAAAAAAAAAAALSEjiYAAAAAAAAAAAC0ZE3cFQDiVG1TQQAAXEBGAQBcRk4BAFxFRgHRY0YTAAAAAAAAAAAAWkJHEwAAAAAAAAAAAFpCRxMAAAAAAAAAAABaQkdTiFgLFHHi+gNQD/cIxInrD8BKuE8gTlx/AOrhHoG4cQ3CRXQ0hWT16tU6d+5c3NVAFzt37pxWr14ddzUAOIiMQtzOnz+vVav4NRRAdeQU4kZbCkAtZBRcQE7BRbTwQ7J+/XqdPn067mqgi50+fVrr16+PuxoAHERGIW4vv/yy1q1bF3c1ADiKnELcaEsBqIWMggvIKbiIjqaQbNq0SQsLC4xyQCzOnTunhYUFbdq0Ke6qAHAQGYU4WWtVLBZ16aWXxl0VAI4ipxAn2lIA6iGjEDdyCq5aE3cFkmrjxo165ZVX9L3vfU+9vb3asGGDVq9eLWNM3FVDQllrde7cOZ0+fVoLCwu69NJLtXHjxrirBcBBZBTiYK3VmTNn9MILL+js2bPq6emJu0oAHEVOIWq0pQA0ioxCHMgpdAI6mkJijNHll1+ul156SS+++KKee+65hkc7nD17VmvWRPdPE2V5nFu45a1evVrr16/X1q1btXHjRn7RAVBVOxkldd+9NQllRV1erbLWrFmjzZs36/LLL2ePJgA10ZaKv6yoy3Ph3GhLAWgEbSk3yuvGcyOn4Do6mkJkjNGmTZuansp44sQJbd++PaRaxVse59a55QFIllYzSuLe2ollRV0eGQWgXbSl4i0r6vKSfG4Akoe2VPzlcW6AexhKCgAAAAAAAAAAgJbQ0QQAAAAAAAAAAICWdMTSecaYYUl9kub8P49Ya6cCOO60tXag3eMAALobOQUAcBUZBQBIurCyDgDQOOc7mowxo5K2WGuzZc+NG2N6rbUTbRw3IykTRB0BAN2LnAIAuIqMAgAkXVhZBwBojtMdTcaYlKQD1tqeipeyko4bYw5Za4stHj678lsAAKiNnAIAuIqMAgAkXchZBwBogut7NA1LOlr5pB8SBUn7WjmoP6V2vL2qAQBATgEAnEVGAQCSLpSsAwA0z/WOpgF5wVBNwX+9Kf5ohwVJjGgAALSLnAIAuIqMAgAkXeBZBwBojesdTXvkbeRXzYKk/haOOcyGgACAgJBTAABXkVEAgKQLI+sAAC1wvaMpVee1oqTeZg5mjOmXNNtWjQAAuICcAgC4iowCACRdoFkHAGid6x1NK6kXKNVkrLX5UGoCAMBy5BQAwFVkFAAg6ZrNOgBAi9bEXYFa/PW/gzzeoKSmlnnwN7od9v962hjzrSDrVMdWSc9HVFbU5XFunVleUsuKurwkn9vOiMpxRtw5FWNGSXxvOrGsqMvj3DqvrKjLi/rcuiqn4s4o/zO0pTq7rKjL49w6s7yklhV1eV2VUUFpJ+toSyWiPM6tM8vj3DqvLKnBnHK2o8laWzTGBHnIXmttrQ0Ca9VhQtJEkJVohDHmqLV2TxLL49w6s7yklhV1eUk+t24Ud07FlVES35tOLCvq8ji3zisr6vLIqHDFnVF+HWhLdXBZUZfHuXVmeUktK47y0Lx2so62VOeXx7l1ZnmcW+eV1YxOXzqvIcaYYT9EAABwDjkFAHAVGQUAAABgJa53NBUlbanxWkrSiqPqjDFpSQtBVgoAAB85BQBwFRkFAEi6trMOABAMZ5fO8+UlpWu8lvZfX0lG0oAxZn/F8ylJMsZM+n8fd2hz26hHDEZZHufWmeUltayoy0vyuXUrcipZZUVdHufWmeUltayoyyOjwkdGJa88zq0zy+PcOq+sOMpDa4LIuqjxvem8sqIuj3PrzPKSWlbDjLU27jrUZIwZlbTfWru7ymtzknKtLuPgb2g7aa0NdPFyAED3IKcAAK4iowAASRdm1gEAmuP60nkTkvqNManyJ/0lHHolHap4PmWMyURYPwBAdyOnAACuIqMAAEnXVNYBAMLj9NJ51tqiMSYrKSdppOylnKSstbZY8ZEH5QXMQANLN/QGWNVAGGOGJfVJmvP/PGKtnQqxrIWwjl+lvFF551Sa0jwe4rmVypK8f+eCtTYbRlk1yp+21g6EcNxJeesLj1trC/4vTv3yRu8MBV1eWbmDkvbrwvr8M0GNCPL/Z8aQpEn/+JXfacm7Tqs93065pe9a6ZfROWvtWJBlVJQ3KKn8mpgO4vpv5Hsc5X2lG3VTTkV9LUWZU1FmVEV5UsQ5FVZG+ceOPKfCzCj/+InPKTIqubopoyTaUiGUJdGWCqLcxLWl/LLJKTihhayLBW2pUMqTaEu1WyZtqfbLIqPKWWudf0galhcSpT8Ha7wvJ++Hm65zrEFJ05JOSrL++yfrfSaicxyVN6W3/LlxScMhlWVr/RxDKG+8/Ocr70Z5Ut5yG2GU1V/x3LS8m2UU55rxvlahHHvG/3crf8xISoV4PrnKfyf/e5gJ6PjDVc6p8hHodeKfU+U1Mhh0OWXHHpf3i0LlNdnW96+R73GU95VufyQ9p6K+lqLMqSgzqqy8WHIqzIzyjx9pToWdUWXHS2xOkVHd8Uh6Rvn1oi0VXFm0pYIrM3FtqbLzIqd4OPVoNOtiqhttqWDLoy0VTHm0pdovi4yqeDi9R1O38Kf4HrfW9lR7XtJVNoDeXWPMuLze/nF5F/6QDbmn0+9dzVtrCxXPZ4Kug3/MVOXxwiirTh2m5d2UA1+v3hiTk3REF0aJzNoQN132/+2GbMVoDWPMSUkTNoARI/41OSdv1EY1+yXdGcT175eXkfdL0LIRGn5dJoP8mZauvcrrwRjTL+nByu98g8ds6Hsc1X0FyRfltRR1TkWZUWXHjS2nwswo//iR5VQUGeUfL7E5RUYhKWhL0ZZq8Ni0pQJATpFTaA5tKdpSTRyftlT75ZFRMWeU00vndZFhSUcrn7TeFOCCpH3y1p1ti7V2cRqxMZHt29tX7Qturc0bY4rypjYHFQQDkoaNMfmKL1Tphpau8pnA+DfqcXmjHEIRduOuQk7eFNdKeXk3vCDUnL7qTxPuDfjmOKDadZ+WN/omyCDPqcr1ba2dNcbIGDPY7L9pE99pb6Q0AAAQDUlEQVTjSO4r6AqRXUsx5FSUGSXFmFNRZJQUaU5FkVFSsnOKjEJS0JYKBm2pYCWxLSWRU+QUmkVbKji0pYJDW6p9ZFQVq+IoFMsMqHbvbkFL13rsNKP+OqPVHJW0J8CyjujCuqLlFkcDBFjWEn6vca31RjuOH6Kq1tNvrR0KcFRFvX+TkWq/tARgpMbzN6v297BV/ap+TUre9b8/4PLKJfm+gmgl+VqKMqOkmHKKjGpLknOKjEJSJPl6oi3VgRLelpLIqU6/ryBaSb6WaEt1INpSgSGjqqCjyQ175E0lrGZB3sXbqWZ1YfO1Sr2q/aVsmrV2ylrbV6U3PKuQl0aQtwZmkjYFHVKV3vGg1fo3Md7mjuMhFHm/pEF/Omql/pD+DWv9MlJUuN/tJN9XEK0kX0uRZZQUa06RUS3qgpwio5AESb6eaEt1pqS2pSRySur8+wqileRribZUZ6ItFRwyqgJL57mh1o1Z8i7O3qgqEjRr7e46L/cr2Gm0yxhjBuX9/PaGWEa/QhzhV6Ws0qiQlCTVmobapj2SDvkjN/aVvxDiyDhJi9Nni5Xr/AbBn8I6Jm/kTUZeL/+CvCmvtUY9tKOo2t/vlMJdgiSx9xVELrHXUtwZJYWfU1FmVFl5YedUbBklJSqnyCgkRWKvp7hzirZUyxLZlpLIKV9H31cQucReS3FnlERbqkW0pYJBRlVBR1NnqHcBdSQ/DCTpYAjHTksalHdDKUraG/ImaJmQGiiVSuuXLt74jTE5Y8x4+TqeASldc8Pl52aMGTXGTFprq63lGpRsCOezyFqbNcbMyRs9MSdv88qwppUeVe1wCXWd+wYk7r6C2CTuWgozo/zjR5lTUWWUFF1OxZlRUnJyioxCt0jc9URbqiW0pQJCTklK4H0FsUnctURbqmW0pQJARkmK8b7C0nkx83uQu1FO0oS1NvCRAdbagrV2zL+RZCU9WBZ0gfKPG9UU2jurTDs9KG8zxMCmRZZdkxlVbB7nh1DGHxkQOP88olr3dkze2qWZOusKtyurKptFhn2eXXxfQcC6+FoKLaOk6HIq4oySIsipODPKLz9JOUVGoeN18fVEW6p5tKWCR04BdXTxtURbqjW0pYJFRsWAjqaYhTw6zEnGmJykQtgjrSQvgCTdKWkypJtlb1jLElSqdq34zxUkHQihnEKN6/OovBtqGA7IW1M1NP5arQVrbdZa2ycvXAeNMTNB37D9X6yy5evD+mXsUbCbEFaW23X3FYSjG6+lKDNKCj2nIssoKZqcijmjpATlFBmFJOjG64m2VGtoSwWHnAIa043XEm2p1tGWCgYZFS86mhApv2d3UN7mc5Hwv/wFeaMqAmOMGY5i/dIGFBTORm+1boxFXVgzNmiDYY16kRY3HJwpHyXi/wI0JO9neE/QZfqjQsaNMcP+iJg9/nWTVojhA6B5cWSUFE5OOZRRUjg5FUdGSQnLKTIK6Cy0pUJBW6oJ5BSAWmhLhYa2VIPIqPixR5MbipK21HgtpYRcnH7P7j2SdsfQA1tQlSmNrfLXhF0I6ngNlDcp6UiNtWHD2Oit3r/PgkJY79O/KYd9XYz4IxqWsNZOGWMGJE2HUagfpJVhmqryXJC64r6CSHTFtRRzRkkB5lTUGeWXGWVORZ5RUnJzioxCAnTF9URbqq3yaEsFh5xK0H0FkeiKa4m2VNtl0pYKBhkV832FjiY35FV/A7HKNTo71aSkoTBCxw+1k/LWga05RdcYkwqo/IykAWPM/ornU345pfU/x6ussdqKQdUPuqBvIvU2tesNoTzJ28gxtJuh/8tCzeNba/PGmEKA18hK0gp3SnK33FcQvm65lkLLKCnynIo6o6RocyqOjJK6K6fIKHSSbrmeaEu1jrZUAMipJWUn5b6C8HXLtURbqj20pdpERi0pO7b7CkvnueGI6l8gMxHWJRT+Oq3ZyvVNjTHDARdV62aRllQM6mZirZ2w1g5VPiSN+6+Xngvqyz1WJ0wz8oIiSJOqfU2G1TMf5vRcyQvtWudUEtg1InlTx6td46WRHNbaMDeWTPx9BZFJ/LUUYUZJEeRUDBklRZtTcWSUlLCcIqOQIIm/nmhLtY22VDDIKU8i7iuITOKvJdpSgaAt1T4yyhPrfYWOJjdMSOqv3JTM743tlXQolloFxP/iTddYhzOQKZn+jWLCWrusx9j/OaYlHQyirJjM+eexhL8GbkrB95QfkpSuVqa8kAvjZxnq9GT/Gin6P7Nl/HMNupE5Iv+XkQoHFO7oBinh9xVEKtHXUhQZJZFTCvaeF0dGScnLKTIKSZHo64m2VCBoSwWAnErOfQWRSvS1RFsqMLSl2kRGuXFfYek8B1hri8aYrLyN68p7sEujAsKa0hf0WtTLGGMy8jZdm67yZd+iYNf+zBljxrX8ZzYuKV9jrdOghfIztdZOGGPGjTG50igR/4YyKW8N0kCvEf+aLN00B0rP+1OEx2r8EtGuUNaBrTAkadIYc2f5Ofg345w/SiVI06oYSeBfo0dtcBtLVr3mYryvIGFivpZCzamIM0qKP6dC+3lGmVMxZZSUvJwio5AItKUCE3dGSbSl2hFFRknkFDmFptCWClTcOUVbqj20pZrXcRllrLVxlY0K/kiAPklz/p9HgpxqZ4wZlXcTKfX2S966jUVJd4ZxIRpjTqr+zSQbZBj4N+ID/l9T8r6UtTbUC4w/NXJE3lTQ0sZrs6oyfbjNcnL+f5bO7WCIIVA6r/3yRh30Sro/rOmfxpg5SVPVRqgEXE7pGikfTTEX1jXif+/65P38UpIm2wmdZr/HYd9X0D2iuJaizqmoM8ovM/Kciiqj/LIiy6koM8ovL3E5RUYhSWhLBVIebakAJbEt5ZdFTgFNoi0VWJm0pYIri7ZU+2WRURXoaAIAAAAAAAAAAEBL2KMJAAAAAAAAAAAALaGjCQAAAAAAAAAAAC2howkAAAAAAAAAAAAtoaMJAAAAAAAAAAAALaGjCQAAAAAAAAAAAC2howkAAAAAAAAAAAAtoaMJAAAAAAAAAAAALaGjCWiBMWbQGDMddz0AAKiGnAIAuIqMAgC4jJwCWmOstXHXAeg4xpgZSf2SBqy1+bjrAwBAOXIKAOAqMgoA4DJyCmgNHU1Ak4wxg5KKkiYlFay1u2OuEgAAi8gpAICryCgAgMvIKaB1LJ0HNO9mf0TDQUn9xphM3BUCAKAMOQUAcBUZBQBwGTkFtIgZTUAT/JENBWvtrP/3k2KEAwDAEeQUAMBVZBQAwGXkFNAeZjQBzbm5FDg+RjgAAFxCTgEAXEVGAQBcRk4BbWBGE9Agf2TDrLW2UPE8IxwAALEjpwAAriKjAAAuI6eA9jGjCWjczZWB48sqISMcjDH9xphBY0x/3HUBADSNnAIAuIqMAgC4jJwC2kRHE9AAY8ywpPFqr1lrJyQVa70eFWNMyhgz59e1pc9LGpE0KelAoJUDAISKnAIAuIqMAgC4jJwCgkFHE9CYvhojG0qyktL+VNs49UpKtfJBa23RWjsiaaqZzzESAgCcQE7VQE4BQOzIqBrIKABwAjlVAzmFZtDRBKyg3siGEn+EQ0FSLpJKVa9D0VrbY60da/NQC02+f3+b5QEA2kBOrYicAoCYkFErIqMAIEbk1IrIKTSMjiZgZakVRjaUuDLCITLGmLRaHE0BAAgMOVUDOQUAsSOjaiCjAMAJ5FQN5BSaRUcTUIc/smGikfdaa6cU8wiHGIzEXQEA6Gbk1IrIKQCICRm1IjIKAGJETq2InEJT6GgC6ktZa4tNvD+2EQ7GmLQxJhPF+qn+JoTDkkbDLgsAUBc5Vb0scgoA4kdGVS+LjAIAN5BT1csip9CSNXFXAHCVMWbU/7OVAMlJmjLG5CQNy5tqWpA0YK0tGGOmJWX89074G/KVyiyNjhiz1mbL6pOTNOf/dbekSWttvqzMcf+YU5KGKs4lJemA//mUpKKko5L2+H9X5Tqv/mf2+X/tkxfApdEMw5Ju9o+TMcZMlj5nrV1SNgAgHOQUOQUAriKjyCgAcBk5RU4heMZaG3cdACcZY06qvbVIh6y1U8aYjKRpSX3l674aY8Ylpa21AxXljqsiUIwxM5LutNbOlj03J2mk4n3jknorb/yV7y1/nx8uGX8a8OJrko6UB5EfLIWKIJyUtFAWRgCAiJBT5BQAuIqMIqMAwGXkFDmF4LF0HlCDtbbHWmvaeEz5x8nLHwVQUcR0leckaa4iSHKSjpYHji8nb0RDXf50194qIyEGjTEpa22xVNcyGS1fp3ZaUtdseggAriOnyCkAcBUZRUYBgMvIKXIKwaOjCYjGIVVMbZWUllSsMk23cn3YUXk3/EpH5a0Nu9IIjN3ypvCWK/19T43PFOzydWoX5I16AAAkDzkFAHAVGQUAcBk5BYg9moCojEuaKY0m8J8ryhtBsF/eGqvyp9yWj2wobfJ3szGm2g0/X+W5aiqDqXSshRrvr/U8ACCZyCkAgKvIKACAy8gpQHQ0AZGw1s4aY4ryNtqb8Ec05OWNUJgpe2t/xXTXtP/n/VWm0UrLp7pWMy1vI79yaUnFGseUlo+wAAAkGDkFAHAVGQUAcBk5BXhYOg+ITvlU2rS1tuDf9Iv+qAZp+c2+FAotT1/112KdNcaMlj2dlXRnq8esxRiTKhuRAQDoLOQUAMBVZBQAwGXkFLoeM5qA6ExKmvbXVy0Pl0OSRowxUsW0WGttwX9+oPI1ybvJV1lXddl7JB30/7s0yiFbZ2RDu9K6EJYAgM5BTgEAXEVGAQBcRk6h6zGjCYiIPz22KOkeLQ2QcUmD8qbQVm7gJ3kjESo3DyypnB5bzR55U2anrLUT/iOoUFjQham+kjcKo9o5AAAcR04BAFxFRgEAXEZOAXQ0AVE7pIpwKU2llbSl2gestWOSCsaY8fLn/am31cKjchPAgqScMSbtT3OtfL2aWu+pfH5SXqiVZEIcNQEACB85BQBwFRkFAHAZOYWuxtJ5QLTGJc1VeX5C0v21PmStHTDGjPrBU/r8bGkTQT9IJiVl/L9PSxqy1hb9qbhHy8v1p+YW5Y2yyPrvSfv1Kz/GiP9a5bHH/dESeWPMQf/1I2L6LAB0OnIKAOAqMgoA4DJyCl3NWGvjrgOAEPmBMG2tnSh7LiVv+uuIpH2Srlpp3VcAAMJATgEAXEVGAQBcRk7BJXQ0AQlmjBmUNGCtHanznmWhBABAFMgpAICryCgAgMvIKbiGPZqAZOtt4D0L/gMAgKiRUwAAV5FRAACXkVNwCh1NQIL5IxbS/iaCy/ijH9LW2qloawYAADkFAHAXGQUAcBk5BdewdB7QBYwxw5L6JL0gb0PAlKQtko4QOACAuJFTAABXkVEAAJeRU3AFHU0AAAAAAAAAAABoCUvnAQAAAAAAAAAAoCV0NAEAAAAAAAAAAKAldDQBAAAAAAAAAACgJXQ0AQAAAAAAAAAAoCV0NAEAAAAAAAAAAKAldDQBAAAAAAAAAACgJf8fhOi8/gVHc80AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3d29b45c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mem_col = 'C3'\n",
    "set_plot_font_size(24)\n",
    "\n",
    "# Quad-plot = default, in thesis.\n",
    "# Non-quad, i.e., line => saves a tiny bit of space for the paper\n",
    "quad_plot = False\n",
    "\n",
    "if quad_plot:\n",
    "    ROWS = 2\n",
    "    COLS = 2\n",
    "else:\n",
    "    ROWS = 1\n",
    "    COLS = 4\n",
    "\n",
    "y_names = {\n",
    "    'accuracy': 'Accuracy',\n",
    "    'completeness': 'Completeness',\n",
    "    'f1': 'F1-Score',\n",
    "    'mem-gb': 'Memory Usage (GiB)'\n",
    "}\n",
    "\n",
    "MAX_GB = 4.5\n",
    "\n",
    "# def mk_acc_mem_plot(ax, stats, depth, key, label):\n",
    "#     ax.plot(stats[depth]['k'], stats[depth][key], label=label)\n",
    "#     ax_mem = ax.twinx()\n",
    "#     mem = np.array(stats[depth]['mem-gb'])\n",
    "    \n",
    "#     ax_mem.bar(stats[depth]['k'], mem, label=\"Memory Usage\", \n",
    "#                color=mem_col, fill=True, alpha=0.5)\n",
    "\n",
    "#     ax_mem.set_ylabel('Memory Usage (GiB)', color=mem_col, labelpad=15)\n",
    "#     ax_mem.set_ylim([0, MAX_GB])\n",
    "#     for i, v in enumerate(mem):\n",
    "#         ax_mem.text(stats[depth]['k'][i] - 0.65, v + 0.05, \"{:.1f} GiB\".format(v),\n",
    "#                     color=mem_col, fontdict={'size': 12})\n",
    "        \n",
    "#     ax.set_ylim([0.4, 1.0])\n",
    "#     ax.set_xlim([-1, 11])\n",
    "#     ax.set_xticks(np.arange(0, 11))\n",
    "#     ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.75)\n",
    "    \n",
    "#     handles1, labels1 = ax.get_legend_handles_labels()\n",
    "#     l = plt.legend(handles1, labels1, loc='lower left')\n",
    "#     ax_mem.add_artist(l)  # Make the legend stay on top\n",
    "    \n",
    "#     ax.set_ylabel(y_names[key], labelpad=10, color='C0')\n",
    "#     ax.set_xlabel(\"$\\Delta_\\\\textrm{weight}$\")\n",
    "#     ax.set_title(label)\n",
    "\n",
    "keys = ['accuracy', 'completeness', 'f1', 'mem-gb']\n",
    "# for key in keys:#, 'mem-gb']):\n",
    "#     fig, (ax_d, ax_e) = plt.subplots(1, 2, figsize=(12, 4))\n",
    "    \n",
    "#     mk_acc_mem_plot(ax_d, stats, 'dispnet', key, \"DispNet\")\n",
    "#     mk_acc_mem_plot(ax_e, stats, 'elas', key, \"ELAS\")\n",
    "    \n",
    "fig, axes = plt.subplots(ROWS, COLS, figsize=(6 * COLS, 6 * ROWS))\n",
    "for ax, key in zip(np.ravel(axes), keys):\n",
    "    ax.plot(stats['elas']['k'], stats['elas'][key], '-x', label='ELAS')\n",
    "    ax.plot(stats['dispnet']['k'], stats['dispnet'][key], '-^', label='DispNet')\n",
    "    \n",
    "    ax.set_xlabel(\"$\\Delta_\\\\textrm{weight}$\")\n",
    "    ax.set_ylabel(y_names[key], labelpad=10)\n",
    "    \n",
    "    if key != 'mem-gb':\n",
    "        ax.set_ylim([0.4, 1.0])\n",
    "    else:\n",
    "        ax.set_ylim(0, MAX_GB)\n",
    "        \n",
    "    ax.set_xlim([-1, 11])\n",
    "    ax.set_xticks(np.arange(0, 11))\n",
    "    ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.75)\n",
    "    ax.xaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.75)\n",
    "    ax.legend(loc='lower left')\n",
    "\n",
    "    \n",
    "#     left  = 0.125  # the left side of the subplots of the figure\n",
    "#     right = 0.9    # the right side of the subplots of the figure\n",
    "#     bottom = 0.1   # the bottom of the subplots of the figure\n",
    "#     top = 0.9      # the top of the subplots of the figure\n",
    "#     wspace = 0.2   # the amount of width reserved for blank space between subplots,\n",
    "#                    # expressed as a fraction of the average axis width\n",
    "#     hspace = 0.2   # the amount of height reserved for white space between subplots,\n",
    "#                    # expressed as a fraction of the average axis height\n",
    "#     fig.subplots_adjust(hspace = 0.5)\n",
    "\n",
    "fig.tight_layout()\n",
    "name = 'recon-acc-flat'#.format(key)\n",
    "\n",
    "fig.savefig(os.path.join(fig_dir, '{}.eps'.format(name)), bbox_inches='tight')\n",
    "fig.savefig(os.path.join(fig_dir, '{}.png'.format(name)), bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
